Partial discharge quantum sensing array optimization layout method and system

Abstract

The invention provides an optimized layout method and system for a partial discharge quantum sensing array, and relates to the technical field of power equipment, and the method comprises the steps: firstly building a dynamic resonance adaptive association rule of a partial discharge signal and a quantum state of a quantum sensing unit; locking a quantum resonance layout domain based on the dynamic resonance adaptive association rule; resonance correspondence between the quantum sensing unit and a partial discharge signal is realized through parameter adjustment of the quantum state regulation and control assembly. Determining the spatial position of each unit according to a multi-unit resonance collaboration corresponding rule; through continuous optimization of a quantum resonance dynamic iteration test, an optimized layout scheme including quantum state resonance adaptive parameters, unit space coordinates, component parameter configuration and operation maintenance requirements is formed, and efficient and accurate detection of partial discharge signals can be realized.

Description

Technical Field

[0001] This invention relates to the field of power equipment technology, and more specifically, to a method and system for optimizing the deployment of a partial discharge quantum sensing array. Background Technology

[0002] In power systems, switchgear is a critical component, and its safe and stable operation is of paramount importance. Partial discharge is a significant precursor and manifestation of insulation degradation in switchgear, and accurate detection and location of partial discharge are of utmost importance for preventing equipment failures and ensuring the reliable operation of power systems.

[0003] Traditional partial discharge detection methods, such as ultrasonic testing and ultra-high frequency testing, can detect partial discharge to a certain extent, but they suffer from limited detection sensitivity and poor anti-interference capabilities. Especially in complex electromagnetic environments and under noise interference, traditional detection methods struggle to accurately capture weak partial discharge signals, leading to inaccurate detection results and failing to promptly identify potential insulation defects in equipment.

[0004] In recent years, quantum sensing technology has demonstrated enormous application potential in the field of partial discharge detection due to its advantages such as high sensitivity and high resolution. However, how to rationally arrange quantum sensing units to form an effective sensing array to fully leverage the advantages of quantum sensing technology and achieve accurate detection and localization of partial discharge signals has become a key issue. Existing sensing array layout methods often lack in-depth consideration of the dynamic resonance relationship between partial discharge signals and quantum sensing units, making it difficult to achieve optimal matching between quantum sensing units and partial discharge signals, resulting in suboptimal detection performance of the sensing array. Summary of the Invention

[0005] In view of the aforementioned problems, and in conjunction with the first aspect of the present invention, the present invention provides a method for optimizing the deployment of a partial discharge quantum sensing array, the method comprising:

[0006] A dynamic resonance adaptation association rule is established between the partial discharge signal of the switching device and the quantum state of the quantum sensing unit. The dynamic resonance adaptation association rule adjusts parameters to make the quantum state energy level of the quantum sensing unit resonate with the physical properties of the partial discharge signal. Based on the dynamic resonance adaptation association rule, the quantum resonance deployment domain of the quantum sensing array is locked. The quantum resonance deployment domain is the spatial range in which the partial discharge signal excites the quantum sensing unit to generate a stable resonance response and the environmental interference has the least effect on the resonance response. By adjusting the parameters of the quantum state control component, the quantum state energy level distribution, energy level transition frequency, and polarization resonance direction of the quantum sensing unit can resonate with the frequency distribution, polarization direction, and transmission path of the partial discharge signal. Based on the multi-unit resonance cooperative correspondence rule in the dynamic resonance adaptation association rule, the corresponding data of the critical value of resonance interference between units, the direction angle and the resonance superposition effect are determined, and the spatial position of each unit in the quantum sensing array is determined so that the resonance response area of ​​each unit jointly covers the target space and the resonance interference between units is lower than the preset threshold. Through dynamic iterative testing of quantum resonance, the spatial position and quantum state control parameters of each unit are continuously optimized to form an optimized layout scheme for the partial discharge quantum sensing array. The optimized layout scheme includes quantum state resonance adaptation parameters, unit spatial resonance coordinates, quantum state control component parameter configuration, and resonance operation and maintenance requirements.

[0007] Furthermore, the present invention also provides a partial discharge quantum sensing array optimized deployment system, comprising: A processor; a machine-readable storage medium for storing machine-executable instructions of the processor; wherein the processor is configured to execute the above-described partial discharge quantum sensing array optimization deployment method by executing the machine-executable instructions.

[0008] In another aspect, the present invention also provides a computer program product, the computer program product including machine-executable instructions, the machine-executable instructions being stored in a computer-readable storage medium, the processor of the partial discharge quantum sensor array optimization deployment system reading the machine-executable instructions from the computer-readable storage medium, the processor executing the machine-executable instructions, causing the partial discharge quantum sensor array optimization deployment system to execute the above-described partial discharge quantum sensor array optimization deployment method.

[0009] Based on the above, by establishing a dynamic resonance adaptation correlation rule between the partial discharge signal of the switching equipment and the quantum state of the quantum sensing unit, a precise resonance response between the quantum state energy level of the quantum sensing unit and the physical properties of the partial discharge signal is achieved, improving the detection sensitivity of the partial discharge signal. Based on this dynamic resonance adaptation correlation rule, the quantum resonance deployment domain is locked, effectively reducing the impact of environmental interference on the resonance response. By adjusting the parameters of the quantum state control components, the quantum state characteristics of the quantum sensing unit and the characteristics of the partial discharge signal achieve a resonance correspondence, further enhancing the accuracy and specificity of signal detection. The spatial position of each unit in the quantum sensing array is determined according to the multi-unit resonance cooperative correspondence rule, ensuring that the resonance response region of each unit jointly covers the target space and that the resonance interference between units is below a preset threshold. This optimizes the overall layout of the sensing array and improves the spatial resolution and anti-interference capability of the detection. Through dynamic iterative quantum resonance testing, the spatial position and quantum state control parameters of each unit are continuously optimized. The resulting optimized deployment scheme comprehensively considers multiple factors such as quantum state resonance adaptation, unit spatial layout, component parameter configuration, and operation and maintenance, enabling high-sensitivity and high-accuracy detection and localization of partial discharge signals, significantly improving the reliability and stability of the power system. Attached Figure Description

[0010] Figure 1 This is a schematic diagram of the execution flow of the partial discharge quantum sensing array optimization deployment method provided in the embodiment of the present invention.

[0011] Figure 2 This is a schematic diagram of exemplary hardware and software components of the partial discharge quantum sensing array optimization deployment system provided in an embodiment of the present invention. Detailed Implementation

[0012] The present invention will now be described in detail with reference to the accompanying drawings. Figure 1 This is a flowchart illustrating a method for optimizing the layout of a partial discharge quantum sensor array according to an embodiment of the present invention. The following is a detailed description of this method.

[0013] Step S110: Establish a dynamic resonance adaptation association rule between the partial discharge signal of the switching device and the quantum state of the quantum sensing unit. The dynamic resonance adaptation association rule adjusts parameters to make the quantum state energy level of the quantum sensing unit resonate with the physical properties of the partial discharge signal.

[0014] In this embodiment, a 10kV switchgear is used as the application scenario. This switchgear contains key components such as circuit breakers and disconnectors, which may experience partial discharge due to insulation defects during operation. To establish the aforementioned dynamic resonance adaptation correlation rules, the system needs to collect the physical properties of the partial discharge signal and combine this with the control parameters of the quantum sensing unit to construct the resonance correspondence between the two. This process involves the collection, analysis, and model building of multi-dimensional data, ultimately forming a set of rules that can guide the adjustment of the quantum sensing unit parameters.

[0015] Step S111: Apply voltage to the switching equipment under different insulation conditions to generate partial discharge signals, collect the partial discharge signals, and record the occurrence time of the partial discharge signals, the time difference of the partial discharge signals arriving at sensors at different spatial locations, and the signal strength measured at each spatial location to form a partial discharge signal physical attribute dataset.

[0016] In this embodiment, insulation defects are simulated on a 10kV switchgear, with different degrees of insulation aging and metal tip defects. A voltage from 0 to 10kV is applied to the switchgear using high-voltage testing equipment, gradually increasing the voltage until a stable partial discharge signal is generated. Multiple traditional electromagnetic sensors are arranged in a three-dimensional grid pattern inside and around the switchgear, with a sensor spacing of 0.5 meters, covering the front, back, left, right, and top areas of the switchgear. When a partial discharge occurs, the time when each sensor detects a signal is recorded, the signal arrival time difference between different sensors is calculated, and the signal strength at each location is measured. For example, sensor A, located 0.5 meters in front of the switchgear, detects a signal at time t1 with a strength of E1; sensor B, located 1 meter on the side of the switchgear, detects a signal at time t2 with a strength of E2. The time difference Δt = t2 - t1 from the discharge point to A and B can be calculated, and the signal propagation path can be deduced by combining the sensor position coordinates. The data collected by all sensors, including the occurrence time, time difference, and signal strength, are compiled to form a partial discharge signal physical attribute dataset, which includes the temporal characteristics, spatial propagation characteristics, and intensity attenuation characteristics of the discharge signal.

[0017] Step S112: Obtain the quantum state control component information of the quantum sensing unit. The quantum state control component information of the quantum sensing unit includes the output wavelength range, output power adjustment range, and linewidth parameters of the laser module, the modulation frequency range and response rate of the frequency locking module, the control bandwidth and adjustment accuracy of the PID module, and the angle adjustment range and response sensitivity parameters of the polarization control component.

[0018] In this embodiment, the selected quantum sensing unit includes a laser module, a frequency-locking module, a PID module, and a polarization control component. The laser module has an output wavelength range of 1550nm to 1560nm, an output power adjustment range of 10mW to 50mW, and a linewidth parameter of 500kHz; the frequency-locking module has a modulation frequency range of 1kHz to 20kHz and a response rate of 10µs; the PID module has a control bandwidth of 16kHz and an adjustment accuracy of 0.1mV; the polarization control component has an angle adjustment range of 0 degrees to 360 degrees and a response sensitivity parameter of 0.1 degrees / second. The parameter information of the above components is organized into structured data, including fields such as component name, parameter type, value range, and unit. For example, the "output wavelength" parameter of the laser module is a numerical type, with a value range of 1550-1560nm, and the unit is nm. This is used to construct a quantum state control component information database.

[0019] Step S113: Test the quantum state energy level distribution of the quantum sensing unit under different quantum state control parameters. By adjusting the output wavelength and power of the laser module, change the energy level spacing of the quantum inside the quantum sensing unit, record the quantum state stable state data corresponding to different energy level spacing, and form the corresponding data of wavelength power and energy level spacing, and the corresponding data of energy level spacing and quantum state stable state.

[0020] In this embodiment, a dedicated quantum state testing platform was built to obtain the quantum state characteristics of the quantum sensing unit under different control parameters. This platform includes a quantum sensing unit fixing device, a laser module parameter adjustment module, a quantum state detection module, a data recording module, and an environmental control module. The quantum sensing unit is fixed in a standard position on the platform. The environmental control module stabilizes the temperature at 25±0.5 degrees Celsius and the humidity at 50±5%RH, simulating the environmental conditions for normal operation of a switchgear. Using the laser module parameter adjustment module, 11 wavelength test points are selected at 1nm intervals within the wavelength range of 1550nm to 1560nm; and 9 power test points are selected at 5mW intervals within the power range of 10mW to 50mW, forming 11×9=99 sets of quantum state control parameter combinations. For each parameter combination, the quantum state detection module is activated, and spectral analysis is used to measure the energy level distribution of quanta within the quantum sensing unit, recording the number of energy levels, the energy value of each energy level, and the size of the energy level intervals. For example, when the wavelength is 1555 nm and the power is 30 mW, three energy levels are detected, with energies Ea, Eb, and Ec, and energy level intervals ΔE1 = Eb - Ea and ΔE2 = Ec - Eb. The stable state of the quantum state under this parameter combination is continuously monitored for 10 minutes, recording the fluctuation values ​​of the energy level intervals (e.g., ΔE1 fluctuates within ±0.01 eV), the drift of the energy level values ​​(e.g., Ea drifts by 0.02 eV within 10 minutes), and the quantum state holding time (e.g., significant fluctuations appear after 8 minutes of stable holding). After organizing all the test data, a table is established to correspond to the quantum state control parameter combinations with energy level distribution and stable state indices. Correlation data between laser wavelength, power, and energy level intervals is extracted from this table to form the correlation data between wavelength / power and energy level intervals; correlation data between energy level intervals and stable state indices (e.g., fluctuation amplitude and drift) is also extracted to form the correlation data between energy level intervals and the stable state of the quantum state.

[0021] Step S1131: Construct a quantum state testing platform, which includes a quantum sensing unit fixing device, a laser module parameter adjustment module, a quantum state detection module, a data recording module, and an environmental control module.

[0022] In this embodiment, the quantum state testing platform must meet high precision and high stability requirements. The quantum sensing unit fixing device adopts an optical breadboard structure, using a precision adjustment bracket to fix the quantum sensing unit, ensuring its spatial position accuracy error does not exceed 0.1mm. The laser module parameter adjustment module includes a wavelength tuner and a power controller. The wavelength tuner achieves continuous wavelength adjustment through voltage control, with an adjustment resolution of 0.01nm; the power controller uses a digital potentiometer to adjust the drive current, achieving precise power control. The quantum state detection module uses a high-resolution spectrometer with a spectral resolution of 0.001nm, capable of capturing spectral signals generated by quantum energy level transitions. The data recording module uses a high-speed data acquisition card with a sampling rate of 1MHz to record changes in the spectral signal over time. The environmental control module includes a temperature control system and a humidity control system, with a temperature control accuracy of ±0.1 degrees Celsius and a humidity control accuracy of ±2%RH. A sealed cover isolates the quantum sensing unit and detection optical path from the external environment. All modules are connected via USB or Ethernet interfaces and are uniformly controlled by host computer software, achieving automation of parameter adjustment, data acquisition, and recording.

[0023] Step S1132: Fix the quantum sensing unit in the standard position of the quantum state test platform, and adjust the temperature and humidity of the test environment through the environmental control module to keep it within the environmental conditions for normal operation of the switching equipment.

[0024] In this embodiment, the quantum sensing unit is fixed to the optical breadboard of the quantum state testing platform using a dedicated clamp. The clamp and breadboard are connected by M6 screws to ensure that the unit does not shift during testing. The temperature sensor of the environmental control module monitors the temperature of the test area in real time. When the temperature deviates from 25 degrees Celsius, the heating or cooling device is activated for adjustment. For example, when the temperature is below 24.5 degrees Celsius, the heating device starts working until the temperature rises back to 25 degrees Celsius; when the temperature is above 25.5 degrees Celsius, the cooling device is activated. Humidity control adopts a combination of dehumidification and humidification. When the humidity is below 45%RH, the humidifier works; when the humidity is above 55%RH, the dehumidifier works, stabilizing the humidity of the test environment at around 50%RH. Before the formal test, the environmental control module needs to run for 30 minutes to ensure that the temperature and humidity reach a stable state, avoiding the influence of environmental fluctuations on the quantum state test results.

[0025] Step S1133: Adjust the output wavelength of the laser module through the laser module parameter adjustment module, and select multiple wavelength test points in sequence from the minimum adjustment range to the maximum adjustment range. Each wavelength test point corresponds to a set of energy level intervals.

[0026] In this embodiment, the output wavelength adjustment range of the laser module is 1550nm to 1560nm, with a minimum adjustment step of 0.1nm. To fully cover this range, starting from 1550nm, 1550nm, 1551nm, ..., 1560nm are selected sequentially at 1nm intervals, for a total of 11 wavelength test points. For each wavelength test point, a control command is sent through the laser module parameter adjustment module to precisely adjust the laser wavelength to the target value. For example, when adjusted to 1553nm, the output wavelength is monitored in real time by a spectrometer. If there is a deviation, feedback adjustment is used to stabilize the wavelength within the range of 1553±0.01nm. Each wavelength test point corresponds to a set of energy level intervals of the quantum inside the quantum sensing unit. For example, 1550nm corresponds to energy level interval ΔEa, 1551nm corresponds to ΔEb, and so on.

[0027] Step S1134: For each wavelength test point, adjust the output power of the laser module, and select multiple power test points sequentially from the minimum output power to the maximum output power to form multiple sets of quantum state control parameter combinations.

[0028] In this embodiment, the output power adjustment range of the laser module is 10mW to 50mW, with a minimum adjustment step of 1mW. At each wavelength test point, starting from 10mW, nine power test points are selected at 5mW intervals: 10mW, 15mW, ..., 50mW. For example, at the 1555nm wavelength test point, the power is adjusted sequentially to 10mW, 15mW, 20mW, 25mW, 30mW, 35mW, 40mW, 45mW, and 50mW. The output power is monitored in real time using a power meter to ensure that the deviation between the actual power and the target power at each power test point does not exceed ±0.5mW. Thus, each wavelength test point combined with the nine power test points forms 11×9=99 sets of quantum state control parameter combinations, covering the main operating parameter range of the laser module.

[0029] Step S1135: Activate the quantum state detection module to detect the energy level distribution of quanta inside the quantum sensing unit under each combination of quantum state control parameters, record the number of energy levels, the energy value of each energy level and the size of the energy level interval, and form the original data of energy level distribution.

[0030] In this embodiment, the quantum state detection module employs a high-resolution spectrometer, whose operating wavelength covers the spectral range of potential energy level transitions that may occur within the quantum sensing unit. For each combination of quantum state control parameters, the spectrometer acquires the output spectral signal of the quantum sensing unit over a period of 1 second, with a spectral resolution set to 0.001 nm. By analyzing the spectral signal, characteristic peaks in the spectrum are identified, each corresponding to a quantum energy level transition, thus determining the number of energy levels. For example, under a certain parameter combination, three distinct characteristic peaks appear in the spectrum, corresponding to three energy levels. Based on the wavelength positions of the characteristic peaks, the energy value of each energy level is calculated using the quantum energy level transition formula, for example, the energy value corresponding to wavelength λ is E=hc / λ (where h is Planck's constant and c is the speed of light). Furthermore, the energy difference between adjacent energy levels, i.e., the energy level interval, such as E2-E1, E3-E2, etc., is calculated. Record data such as the number of energy levels, the energy value of each energy level, and the energy level interval to form the original data of energy level distribution. Each data entry contains fields such as parameter combination identifier (wavelength, power), number of energy levels, energy value list, and energy level interval list.

[0031] Step S1136: Based on the original energy level distribution data, continuously detect the stable state of the quantum state under each set of parameters, record the fluctuation data of the energy level interval, the drift data of the energy level value and the quantum state holding time within a preset time, and form the original stable state data.

[0032] In this embodiment, for each set of quantum state control parameters, after the energy level distribution detection is completed, the parameters are kept unchanged, and the stable state of the quantum state is continuously monitored for 10 minutes. The energy level interval and energy value are recorded every 10 seconds, for a total of 60 sets of data. The difference between the maximum and minimum values ​​of each energy level interval within 10 minutes is calculated as the fluctuation data of the energy level interval; the difference between the initial and final values ​​of each energy level energy value within 10 minutes is calculated as the drift data of the energy level energy value. Simultaneously, the time from quantum state stability to significant instability (e.g., energy level interval fluctuation exceeding ±0.02 eV) is observed and recorded as the quantum state holding time. For example, under a certain parameter combination, the energy level interval fluctuates from 0.5 eV to 0.51 eV within 10 minutes, with a fluctuation data of 0.01 eV; the initial energy level energy value is 2.0 eV, and the final value is 2.01 eV, with a drift data of 0.01 eV; the quantum state holding time is 8 minutes, after which the fluctuation amplitude exceeds the threshold. The above data is recorded to form the original data of the stable state, which is then stored in association with the original data of the energy level distribution.

[0033] Step S1137: Based on the original stable state data, calculate the stable state index of the quantum state under each set of parameters. The stable state index is a comprehensive quantitative result of the fluctuation data of the energy level interval and the drift data of the energy level energy value.

[0034] In this embodiment, the steady-state index is calculated using a weighted summation method, transforming the fluctuation data of the energy level interval and the drift data of the energy level value into a comprehensive quantitative value. The weight of the energy level interval fluctuation is set to 0.6, and the weight of the energy level value drift is set to 0.4. First, the fluctuation data and drift data are normalized, mapping them to the range of 0 to 1. For example, if the maximum value of the fluctuation data is 0.05 eV, then the normalized fluctuation value for a certain set of data = fluctuation data / 0.05; if the maximum value of the drift data is 0.03 eV, then the normalized drift value = drift data / 0.03. Then, the steady-state index = 0.6 × fluctuation normalized value + 0.4 × drift normalized value. The smaller the index value, the more stable the quantum state. For example, if the fluctuation data of a certain parameter combination is 0.01 eV, the normalized value is 0.01 / 0.05 = 0.2; the drift data is 0.01 eV, and the normalized value is 0.01 / 0.03 ≈ 0.333; then the stable state index = 0.6 × 0.2 + 0.4 × 0.333 ≈ 0.12 + 0.133 = 0.253. This value is relatively small, indicating that the quantum state stability is good.

[0035] Step S1138: Based on the original energy level distribution data, the original steady-state data, and the steady-state index, establish a table showing the correspondence between the quantum state control parameter combination, the quantum state energy level distribution, and the steady-state index.

[0036] In this embodiment, the correspondence table is in two-dimensional form. Rows represent different wavelength test points, and columns represent different power test points. Each cell contains information on the quantum state energy level distribution (number of energy levels, energy values ​​of each energy level, energy level interval), raw stable state data (fluctuation data, drift data, holding time), and stable state indices for that wavelength-power combination. For example, the cell with a wavelength of 1555nm and a power of 30mW records the following information: number of energy levels 3, energy values ​​E1, E2, and E3, energy level intervals ΔE1=E2-E1 and ΔE2=E3-E2, fluctuation data 0.01eV, drift data 0.01eV, holding time 8 minutes, and stable state index 0.253. This correspondence table intuitively demonstrates the influence of different combinations of control parameters on the quantum state.

[0037] Step S1139: Based on the correspondence table, extract the correlation data of laser module output wavelength, output power and energy level spacing to form the correspondence data of wavelength power and energy level spacing.

[0038] In this embodiment, energy level interval data for each wavelength-power combination is extracted from the correspondence table to construct a three-dimensional data set of wavelength, power, and energy level interval. For example, a wavelength of 1550nm and a power of 10mW correspond to an energy level interval ΔE1_1, a wavelength of 1550nm and a power of 15mW correspond to ΔE1_2, and so on. The above data is organized into an array, where the first dimension is wavelength, the second dimension is power, and the third dimension is the energy level interval value. Through data fitting methods, a mathematical relationship between wavelength, power, and energy level interval is established, for example, ΔE=a×λ+b×P+c (where a, b, and c are fitting coefficients, λ is wavelength, and P is power), forming the corresponding data of wavelength, power, and energy level interval. The size of the energy level interval can be predicted based on the wavelength and power.

[0039] Step S11310: Based on the correspondence table, extract the correlation data between energy level intervals and stable state indices to form the correspondence data between energy level intervals and quantum state stable states.

[0040] In this embodiment, the stable state index corresponding to each energy level interval is extracted from the correspondence table to construct a two-dimensional dataset of energy level intervals and stable state indices. For example, an energy level interval of 0.4 eV corresponds to a stable state index of 0.3, 0.5 eV corresponds to 0.25, and 0.6 eV corresponds to 0.35, etc. By plotting a scatter plot to observe the relationship between the two, a certain nonlinear relationship is found. A polynomial fitting method is used to establish a functional relationship between energy level intervals and stable state indices, such as stable state index = d × ΔE² + e × ΔE + f (where d, e, and f are fitting coefficients), forming the corresponding data of energy level intervals and quantum state stable states. The stability of the quantum state can be predicted based on the energy level interval.

[0041] Step S114: Compare the frequency range in the partial discharge signal physical property data set with the quantum state energy level transition frequency. Based on the corresponding data of wavelength power and energy level interval, adjust the output wavelength of the laser module to change the quantum state energy level transition frequency, determine the energy level transition frequency range that enables the quantum sensing unit to generate a resonant response to the partial discharge signal, and establish the correspondence between frequency and energy level.

[0042] In this embodiment, the frequency characteristics of the signal are first extracted from the physical property dataset of the partial discharge signal. The time-domain signal is converted into a frequency-domain signal using Fourier transform to obtain the frequency distribution range of the partial discharge signal, for example, 50MHz to 500MHz. The relationship between the quantum state energy level transition frequency and the energy level spacing is f=ΔE / h (where h is Planck's constant), so the energy level transition frequency can be calculated based on the energy level spacing. Based on the corresponding data of wavelength power and energy level spacing obtained in step S1139, the energy level spacing is changed by adjusting the output wavelength of the laser module, thereby changing the energy level transition frequency. For example, when it is necessary to adjust the energy level transition frequency to 200MHz, the required energy level spacing ΔE=h×f is calculated according to f=ΔE / h, and the corresponding laser wavelength and power are determined according to the corresponding data of wavelength power and energy level spacing. Through multiple adjustment tests, it was found that when the energy level transition frequency of the quantum sensing unit falls within the 50MHz to 500MHz range, a significant resonance response (manifested as a significant increase in response intensity) is generated for the partial discharge signal. Therefore, this range is determined to be the resonant energy level transition frequency range. Record the energy level spacing, laser wavelength, and power parameters corresponding to different frequency values ​​to establish the correspondence between frequency and energy level, that is, a specific frequency corresponds to a specific energy level spacing and control parameters.

[0043] Step S115: Compare the polarization direction in the partial discharge signal physical property dataset with the polarization resonance direction of the quantum sensing unit, adjust the angle of the polarization control component to change the polarization resonance direction of the quantum state, determine the range of polarization angles that enable the quantum sensing unit to generate a resonance response to the partial discharge signal, and establish the correspondence between the polarization direction and the polarization direction.

[0044] In this embodiment, the partial discharge signal physical property dataset contains the polarization direction information of the signal. The polarization direction of the signal is measured to vary from 0 to 180 degrees using a polarization detection device. The polarization resonance direction of the quantum sensing unit is determined by the angle of the polarization control component. Adjusting the angle of the polarization control component can change the polarization resonance direction of the quantum state. During the test, the wavelength and power parameters of the laser module are fixed so that the energy level transition frequency is within the resonance frequency range. Then, the angle of the polarization control component is gradually adjusted from 0 to 360 degrees, and the response intensity of the quantum sensing unit to the partial discharge signal is recorded every 5 degrees. When the angle of the polarization control component is consistent with the polarization direction of the signal, the response intensity reaches its maximum value; when they are perpendicular, the response intensity is minimum. Through testing, it was found that when the polarization angle is within ±15 degrees of the polarization direction of the signal, the response intensity remains above 80% of the maximum value. Therefore, this range is determined as the polarization angle range. The angle of the polarization control component corresponding to different signal polarization directions is recorded to establish the correspondence between the polarization direction and the polarization direction. For example, when the signal polarization direction is 30 degrees, the angle of the polarization control component should be set between 15 and 45 degrees.

[0045] Step S116: Extract the transmission attenuation data from the partial discharge signal physical property dataset, combine it with the corresponding data of energy level interval and quantum state stable state, analyze the change of quantum state resonance response intensity with signal propagation distance, determine the minimum intensity of partial discharge signal required for the quantum sensing unit to generate an effective resonance response, and establish the correspondence between signal propagation distance, signal intensity and resonance response intensity.

[0046] In this embodiment, the transmission attenuation data in the partial discharge signal physical property dataset shows that the signal strength decreases with increasing propagation distance. For example, the signal strength at 1 meter from the discharge point is E0, and at 2 meters it is E0×k (k is the attenuation coefficient, k<1). Combining the corresponding data of energy level spacing and quantum state stability obtained in step S11310, when the signal strength is strong, the quantum state resonance response strength is high and stable; when the signal strength weakens to a certain extent, the response strength decreases significantly and the stability decreases. By placing quantum sensing units at different propagation distances (such as 0.5 meters, 1 meter, 1.5 meters, 2 meters, etc.) and measuring their resonance response strength, it was found that when the signal strength drops to a certain value Emin, the resonance response strength drops to 50% of the maximum response strength, and the stability index exceeds 0.5 (considered unstable). Therefore, Emin is determined as the minimum signal strength required for an effective resonance response. According to the transmission attenuation law, the relationship between signal propagation distance d and signal strength E can be obtained as E=E0×k^d. Combining the resonance response intensity at different distances, the correspondence between signal propagation distance, signal strength and resonance response intensity can be established. For example, the signal strength E at distance d corresponds to the resonance response intensity R.

[0047] Step S117: Collect temperature, humidity, and electromagnetic interference data of the operating environment of the switching equipment, record the offset data of quantum state energy level transition frequency under different environmental conditions, and establish the resonance correction correspondence between the environment and the quantum state.

[0048] In this embodiment, temperature sensors, humidity sensors, and electromagnetic interference detectors are deployed in the switchgear operating environment to collect data on temperature (range -10 to 50 degrees Celsius), humidity (range 20% to 90%RH), and electromagnetic interference (frequency range 1MHz to 1GHz, intensity range 0 to 100dBμV / m). Under different environmental conditions, the control parameters of the quantum sensing unit are kept constant, and the shift in the quantum state energy level transition frequency is measured. For example, when the temperature increases from 25 degrees Celsius to 35 degrees Celsius, the energy level transition frequency shifts by +5MHz; when the humidity increases from 50%RH to 70%RH, the shift is +2MHz; and when the electromagnetic interference intensity increases from 30dBμV / m to 50dBμV / m, the shift is -3MHz. Through a large amount of test data, a multivariate functional relationship Δf=g(T, H, I) between environmental parameters (temperature T, humidity H, electromagnetic interference intensity I) and the energy level transition frequency shift Δf is established, forming a resonance correction correspondence between the environment and the quantum state. When environmental conditions change, the frequency offset can be calculated based on this relationship, and compensation can be made by adjusting parameters such as the wavelength of the laser module to maintain the resonant response.

[0049] Step S118: Based on the correspondence between frequency and energy level, the correspondence between polarization direction and polarization direction, the correspondence between signal propagation distance and signal intensity and resonance response intensity, and the resonance correction correspondence between environment and quantum state, a single-unit quantum state resonance adaptation correspondence model is constructed. The single-unit quantum state resonance adaptation correspondence model describes the resonance interaction mode between a single quantum sensing unit and the partial discharge signal.

[0050] In this embodiment, the single-unit quantum state resonance adaptation model is constructed using a system of mathematical equations. The model inputs include the frequency f, polarization direction P, and propagation distance d of the partial discharge signal, as well as environmental parameters T, H, and I. The outputs include the laser wavelength λ, power Pw, and polarization angle θ of the quantum sensing unit, and the expected resonance response intensity R. Internally, the model determines the required energy level spacing ΔE from the signal frequency f based on the correspondence between frequency and energy levels, and then determines the wavelength λ and power Pw based on the correspondence between wavelength power and energy level spacing. It also determines the polarization angle θ from the signal polarization direction P based on the correspondence between polarization direction and polarization direction. Furthermore, it calculates the frequency offset Δf based on the environmental parameters T, H, and I, and corrects the wavelength λ, based on the resonance correction correspondence between the environment and the quantum state, and predicts the resonance response intensity R based on the correspondence between the signal propagation distance d and the signal intensity and resonance response intensity. For example, when the input signal frequency f = 200 MHz, polarization direction P = 30 degrees, propagation distance d = 1 meter, ambient temperature T = 30 degrees Celsius, humidity H = 60%RH, and electromagnetic interference I = 40 dBμV / m, the model calculates the energy level spacing ΔE = h × f. Based on the wavelength power and corresponding energy level spacing data, the initial wavelength λ0 and power Pw are determined. Then, the frequency offset Δf is calculated based on the environmental parameters, and the wavelength is corrected to λ = λ0 + Δλ (Δλ is the wavelength correction amount corresponding to Δf). The polarization angle θ = 30 ± 15 degrees, and the predicted resonant response intensity R = R0 × k^d (R0 is the response intensity at a distance d = 0). This model fully describes the resonant interaction between a single quantum sensing unit and the partial discharge signal.

[0051] Step S119: Based on the single-unit quantum state resonance adaptation model, a resonance signal superposition model is introduced when multiple quantum sensing units work simultaneously. The mutual interference data of quantum state resonance between adjacent units is obtained through testing. The minimum allowable unit spacing and / or polarization direction angle range when the resonance interference between units is lower than a preset threshold is determined, and a multi-unit resonance cooperative correspondence rule is established.

[0052] In this embodiment, the establishment of multi-unit resonance synergy correspondence rules needs to consider the mutual influence when multiple quantum sensing units work simultaneously. First, a multi-unit synergy resonance test platform is built, including three quantum sensing units, a partial discharge signal simulation device, a resonance signal acquisition device, and an interference analysis device. Based on the single-unit quantum state resonance adaptation correspondence model, initial control parameters for each unit are set. Two units, A and B, are installed on the test platform; A is fixed in position, while B can move along a guide rail to change the spacing. At different spacings (e.g., 0.5 m, 1 m, 1.5 m, 2 m, etc.), the signal simulation device is activated to generate standard partial discharge signals, and the resonance response data of A and B are collected. When the spacing is small (e.g., 0.5 m), the resonance signals of the two units superimpose, causing fluctuations in response intensity (interference); as the spacing increases, the interference gradually decreases. The interference intensity is defined as the absolute value of the difference between the superimposed response intensity and the response intensity of a single unit, and the preset interference threshold is 10% of the maximum response intensity of a single unit. Through testing, it was found that when the spacing is greater than 1.2 m, the interference intensity is below the threshold; therefore, the minimum unit spacing is determined to be 1.2 m. Furthermore, by changing the polarization angle between the two units (0 degrees, 30 degrees, 60 degrees, 90 degrees, etc.), it was found that the interference intensity was minimal when the angle was 90 degrees. Based on the test results of spacing and angle, a multi-unit resonance coordination rule was established, stipulating that the unit spacing should not be less than 1.2 meters, or that the spacing can be reduced to 0.8 meters when the polarization angle is 90 degrees.

[0053] For example, step S1191: build a multi-unit cooperative resonance test platform, which includes multiple quantum sensing units, a partial discharge signal simulation device, a resonance signal acquisition device, and an interference analysis device.

[0054] In this embodiment, the multi-unit coordinated resonance test platform is built in an electromagnetically shielded room to avoid external interference. The platform includes three identical quantum sensing units, each equipped with an independent control module and signal output interface. A partial discharge signal simulation device can generate pulsed electromagnetic field signals with frequencies ranging from 50MHz to 500MHz and polarization directions from 0 to 180 degrees, with continuously adjustable signal strength. The resonance signal acquisition device uses a multi-channel data acquisition card with a sampling rate of 200MHz, capable of simultaneously acquiring the output signals of the three units. The interference analysis device is a computer running dedicated analysis software, connected to the data acquisition card via Ethernet, to calculate the interference intensity between units in real time. The quantum sensing units are mounted on a three-dimensional adjustable bracket, allowing for precise adjustment of position and angle, with a position adjustment accuracy of 0.1mm and an angle adjustment accuracy of 0.1 degrees. The platform also includes a synchronization trigger module to ensure the synchronized operation of the signal simulation device, data acquisition card, and quantum sensing units.

[0055] Step S1192: Based on the single-unit quantum state resonance adaptation model, set the quantum state control parameters for each quantum sensing unit.

[0056] In this embodiment, for a simulated partial discharge signal (frequency 200MHz, polarization direction 30 degrees), the control parameters of each quantum sensing unit are calculated based on the single-unit quantum state resonance adaptation model. For example, the model outputs a laser wavelength of 1555nm, a power of 30mW, and a polarization angle of 30 degrees. Through the control module of each unit, the laser module wavelength is set to 1555nm, the power to 30mW, and the polarization control component angle to 30 degrees. The quantum state detection module is activated to verify whether the energy level transition frequency of each unit is 200MHz and whether the polarization resonance direction is 30 degrees, ensuring the accuracy of the control parameter settings. If there are deviations, corrections are made by fine-tuning the wavelength or polarization angle to ensure that each unit is in a resonant state with the target signal.

[0057] Step S1193: Install two quantum sensing units on a multi-unit synergistic resonance test platform, keep the position of one unit fixed, and gradually adjust the spatial position of the other unit to change the distance between the two units.

[0058] In this embodiment, unit A is fixed at the coordinate origin (0, 0, 0) of the test platform, and unit B is mounted on a movable guide rail extending along the X-axis. The X-coordinate of unit B is gradually changed via a guide rail drive device, thereby altering the distance between A and B. The distance adjustment range is 0.3 meters to 3 meters, with an adjustment step of 0.1 meters. At each distance, the actual distance between A and B is measured using a laser rangefinder to ensure the distance error does not exceed 0.01 meters. The height (Y-coordinate) and depth (Z-coordinate) of units A and B are kept consistent, both being (0, 0.5, 0) and (x, 0.5, 0), respectively, ensuring they are on the same horizontal plane and avoiding the influence of height difference on signal propagation.

[0059] Step S1194: Under each spacing setting, start the partial discharge signal simulation device to generate a standard partial discharge signal, and record the resonance response data of the two units through the resonance signal acquisition device to form a dual-unit spacing response dataset.

[0060] In this embodiment, the standard partial discharge signal is set to a frequency of 200MHz, a polarization direction of 30 degrees, and a signal strength of E0 (measured at a distance of 1 meter from the signal source). At each spacing position, the signal simulation device is activated, continuously outputting a signal for 10 seconds. Simultaneously, the resonant signal acquisition device is activated to synchronously acquire the output voltage signals of units A and B at a sampling rate of 1MHz. The acquired signals are filtered to remove noise, and then the resonant response intensity (such as the peak voltage of the signal) of each unit is calculated. The spacing value, the response intensity of unit A, the response intensity of unit B, and other data are recorded to form a dual-unit spacing response dataset. For example, when the spacing is 0.5 meters, the response intensity of A is 5V and the response intensity of B is 4.8V; when the spacing is 1.2 meters, the response intensity of A is 5V and the response intensity of B is 5V, etc.

[0061] Step S1195: Based on the two-element spacing response dataset, measure the resonance response intensity of the two elements at different spacings, record the change of resonance response intensity with spacing, identify the spacing range where the resonance superposition effect is significant, and form the corresponding data of element spacing and resonance superposition effect.

[0062] In this embodiment, the response intensities of A and B at different spacings are extracted from the two-unit spacing response dataset, and the response intensity variation curves with spacing are plotted. When the spacing is small, the resonance signals of the two units superimpose, resulting in constructive interference (enhanced response intensity) or destructive interference (weakened response intensity), i.e., resonance superposition effect. For example, at a spacing of 0.5 meters, the response intensity of B (4.8V) is lower than that of A (5V), exhibiting destructive interference; at a spacing of 0.8 meters, the response intensity of B (5.5V) is higher than that of A (5V), exhibiting constructive interference. By analyzing the curves, the spacing range in which the resonance superposition effect is significant is determined to be 0.3 meters to 1.0 meters, within which the response intensity fluctuates by more than ±10%. The superposition effect type (enhanced or weakened) and intensity variation amplitude corresponding to different spacings are recorded to form the corresponding data of unit spacing and resonance superposition effect.

[0063] Step S1196: Change the polarization resonance direction of the fixed unit, continue the test process, and record the resonance response data of the two units under different directional angles to form a dual-unit angle response dataset.

[0064] In this embodiment, the polarization resonance direction of unit A is fixed at 30 degrees, and the polarization direction of unit B is gradually adjusted from 0 degrees to 180 degrees in 15-degree intervals, for a total of 13 angle test points. At each angle, the unit spacing is maintained at 1.2 meters (the previously determined minimum interference-free spacing), and the signal simulation device and data acquisition device are activated to record the response intensity of A and B. For example, when the polarization direction of B is 0 degrees, the response intensity is 4.5V; at 30 degrees (in the same direction as A), the response intensity is 5.2V; at 90 degrees, the response intensity is 5V; and at 180 degrees, the response intensity is 4.3V. The angle values, the response intensity of A, and the response intensity of B are recorded to form a dual-unit included-angle response dataset.

[0065] Step S1197: Based on the dual-unit angle response dataset, analyze the effect of the directional angle on the resonance superposition effect, and record the corresponding data of the directional angle and the resonance superposition effect.

[0066] In this embodiment, the response intensity at different directional angles is extracted from the dual-unit angle response dataset. Analysis reveals that the superposition effect is strongest (response intensity 5.2V) when the polarization angle between the two units is 0 degrees (in the same direction); the superposition effect is weakest (response intensity 4.3V) when the angle is 180 degrees (in opposite directions); and the superposition effect essentially disappears (response intensity 5V, the same as a single unit) when the angle is 90 degrees. The magnitude of response intensity variation corresponding to different directional angles is recorded to form corresponding data on the directional angle and resonance superposition effect, such as a 4% increase at 0 degrees, no change at 90 degrees, and a 14% decrease at 180 degrees.

[0067] Step S1198: Increase the number of test units to three, install them according to different spatial arrangements, repeat the test process, integrate the corresponding data of unit spacing, directional angle and resonance superposition effect to form a multi-unit collaborative response dataset.

[0068] In this embodiment, unit C is added to form a triangular arrangement with units A and B. Different spatial arrangements are set, including A(0,0,0), B(1.2,0,0), C(0.6,1.04,0) (an equilateral triangle with a side length of 1.2 meters), and linear arrangements such as A(0,0,0), B(1.2,0,0), C(2.4,0,0). Under each arrangement, the spacing between units and the polarization angle are varied, and the signal acquisition and data recording process in the dual-unit test is repeated. For example, under the equilateral triangular arrangement, the influence of the spacing between units A and C, and the spacing between units B and C, on the response intensity is tested; under the linear arrangement, the effect of the angles between unit B and A and C on the superposition effect is tested. All test data are integrated to form a multi-unit collaborative response dataset, containing response intensity data of the three units under different arrangements, spacings, and angles.

[0069] Step S1199: Based on the multi-unit collaborative response dataset, establish a model corresponding to the multi-unit resonance superposition effect to describe the correspondence between unit spacing, directional angle, number of units and resonance superposition intensity.

[0070] In this embodiment, the model corresponding to the multi-unit resonance superposition effect is constructed using a multiple regression analysis method. The unit spacing *d*, the directional angle *θ*, and the number of units *n* are used as independent variables, and the resonance superposition intensity ΔR (the difference between the superimposed response intensity and the response intensity of a single unit) is used as the dependent variable. By fitting data from the multi-unit coordinated response dataset, the model equation ΔR = k1×d + k2×cosθ + k3×n + k4 (where k1, k2, k3, and k4 are regression coefficients) is obtained. For example, the fitting results might be k1 = -0.5 (increasing spacing decreases superposition intensity), k2 = 0.8 (increasing the cosine value of the angle, i.e., decreasing the angle, increases superposition intensity), k3 = 0.3 (increasing the number of units increases superposition intensity), etc. This model can predict the resonance superposition intensity based on the unit spacing, directional angle, and number of units.

[0071] Step S11910: Based on the multi-unit resonance superposition effect corresponding model, analyze the mutual interference process of quantum state resonance between adjacent units, mark the physical process and influencing factors of interference, and record the corresponding trend of interference intensity with unit spacing and directional angle.

[0072] In this embodiment, the mutual interference of quantum state resonance between adjacent units mainly originates from the electromagnetic coupling between quantum states. When the distance between two units is small, the electromagnetic field generated by the quantum state transition of one unit will disturb the quantum state of the other unit, causing a shift in the energy level transition frequency, thereby affecting the resonance response. Influencing factors include unit spacing (the smaller the spacing, the stronger the coupling and the greater the interference), directional angle (the coupling is strongest when in the same direction and weakest when perpendicular), and signal strength (the stronger the signal, the more significant the coupling). Through analysis of the multi-unit resonance superposition effect corresponding model, it was found that the interference intensity decreases exponentially with the increase of the spacing and decreases linearly with the directional angle from 0 degrees to 90 degrees. For example, for every 0.3 meters increase in spacing, the interference intensity decreases by 50%; for every 30 degrees increase in angle, the interference intensity decreases by 20%. The above trend data are recorded as the basis for determining the critical value of interference.

[0073] Step S11911: Based on the corresponding trend of interference intensity and unit spacing and directional angle, the critical value of inter-unit resonance interference is determined by statistical analysis of multiple sets of test data. The critical value of inter-unit resonance interference is the minimum unit spacing and the optimal directional angle combination when the interference intensity drops to a set negligible range.

[0074] In this embodiment, the negligible range of interference intensity is set to 5% of the maximum response intensity of a single unit. Statistical analysis of multiple sets of test data shows that when the unit spacing is 1.5 meters, the interference intensity is below 5% regardless of the directional angle; when the spacing is 1.0 meter and the directional angle is 90 degrees, the interference intensity is also below 5%. Therefore, the critical values ​​for inter-unit resonance interference include: a minimum unit spacing of 1.5 meters (any angle), or a minimum unit spacing of 1.0 meter and a directional angle of 90 degrees.

[0075] Step S11912: Integrate the corresponding model of multi-unit resonance superposition effect and the critical value of inter-unit resonance interference, and output the corresponding rule and critical numerical parameters of multi-unit resonance synergy.

[0076] In this embodiment, the multi-unit resonance coordination rule integrates model prediction and critical values. Specifically, the rules include: the spacing between adjacent units in the quantum sensing array should be no less than 1.5 meters; if space constraints prevent achieving a 1.5-meter spacing, the polarization angle between adjacent units can be set to 90 degrees, reducing the minimum spacing to 1.0 meter; when the number of units exceeds three, a triangular or other symmetrical arrangement should be used to avoid multi-unit superposition interference; during layout, both spacing and angle must be considered, prioritizing ensuring the spacing meets the critical value, and then adjusting the angle to further reduce interference. Critical value parameters include: minimum spacing of 1.5 meters (arbitrary angle), minimum spacing of 1.0 meter (90-degree angle), and an interference intensity threshold of 5%. These rules and parameters are compiled into a structured document as part of the dynamic resonance adaptation association rules.

[0077] Step S1110: Integrate the partial discharge signal physical property dataset, quantum state modulation component information of quantum sensing unit, single-unit quantum state resonance adaptation correspondence model and multi-unit resonance cooperative correspondence rules to form dynamic resonance adaptation association rules, and output a structured representation containing corresponding data of resonance correspondence parameters, resonance adjustment threshold, resonance cooperative constraint values, direction angle and resonance superposition effect.

[0078] In this embodiment, the integration of dynamic resonance adaptation association rules adopts a hierarchical structure. The first layer is the basic data layer, which includes the physical attribute dataset of partial discharge signals (frequency range, polarization direction, transmission attenuation, etc.) and the quantum state control component information of the quantum sensing unit (parameters such as laser module and frequency locking module). The second layer is the model layer, which includes the single-unit quantum state resonance adaptation corresponding model and the multi-unit resonance cooperative correspondence rules. The third layer is the parameter layer, which includes resonance correspondence parameters (frequency-energy level, polarization-polarization correspondence), resonance adjustment thresholds (minimum signal strength Emin, stable state index threshold, etc.), resonance cooperative constraint values ​​(minimum unit spacing, angle range, etc.), and the corresponding data of direction angle and resonance superposition effect. The structured representation of the output adopts XML format, for example:<dynamicresonancerule> <basicdata> <signalproperty> <frequencyrange> 50MHz-500MHz< / frequencyrange> ...< / signalproperty> <sensorinfo> <lasermodule> <wavelengthrange> 1550nm-1560nm< / wavelengthrange> ...< / lasermodule> ...< / sensorinfo> < / basicdata> <models> <singleunitmodel> ...< / singleunitmodel> <multiunitrule> ...< / multiunitrule> < / models> <parameters> <resonanceparams> ...< / resonanceparams> ...< / parameters> < / dynamicresonancerule> This structured document can be directly parsed and used by the system in subsequent steps.

[0079] Step S120: Based on the dynamic resonance adaptation association rule, lock the quantum resonance deployment domain of the quantum sensing array. The quantum resonance deployment domain is the spatial range in which the partial discharge signal excites the quantum sensing unit to generate a stable resonance response and the environmental interference has the least effect on the resonance response.

[0080] In this embodiment, in the application scenario of a 10kV switchgear, the locking of the quantum resonance deployment domain needs to comprehensively consider the structural characteristics of the switchgear, the propagation law of partial discharge signals, and the distribution of environmental interference. By analyzing the data and models in the dynamic resonance adaptation association rules, a spatial region is determined in which the quantum sensing units can stably respond to the partial discharge signals, with minimal environmental interference, while also satisfying the constraints of multi-unit collaborative deployment. This process involves multiple steps, including three-dimensional spatial modeling, signal propagation simulation, and environmental interference analysis, ultimately outputting a clear spatial coordinate range and related attribute parameters.

[0081] Step S121: Obtain the three-dimensional structural model data of the switchgear. The three-dimensional structural model data of the switchgear includes the spatial position of the internal components, the electromagnetic conductivity coefficient of the component materials, the shielding parameters of the external shell, and the coordinates of key parts that are prone to partial discharge.

[0082] In this embodiment, a 10kV switchgear is scanned using 3D scanning technology to obtain its 3D structural model data. The model data is stored in STL format and includes a 3D mesh model of the switchgear's outer shell, internal circuit breakers, disconnectors, busbars, and other components. For each component, its spatial coordinates (based on a 3D coordinate system with the center of the switchgear's bottom as the origin) are recorded. For example, the circuit breaker is located in a spatial range of (0.5m, 0.8m, 0.3m) to (0.8m, 1.2m, 0.6m). The electromagnetic conductivity coefficients of the component materials are obtained from material handbooks. For example, the electromagnetic conductivity coefficient of copper busbars is σ1, and the electromagnetic conductivity coefficient of insulating partitions is σ2 (σ2 is much smaller than σ1). The shielding parameters of the outer shell include shielding effectiveness (e.g., 40dB at 100MHz) and thickness (2mm). Key locations prone to partial discharge are identified through statistical analysis of historical fault data, including circuit breaker contacts, disconnector blades, busbar joints, etc. The coordinates of these locations are recorded; for example, the coordinates of the circuit breaker contacts are (0.65m, 1.0m, 0.45m).

[0083] Step S122: Extract the correspondence between signal propagation distance, signal intensity and resonance response intensity in the dynamic resonance adaptation association rules, define the minimum partial discharge signal intensity required for the quantum sensing unit to generate an effective resonance response, and calculate the maximum propagation distance corresponding to the effective resonance response by combining the transmission attenuation data in the partial discharge signal physical attribute dataset in the dynamic resonance adaptation association rules.

[0084] In this embodiment, the correspondence between signal propagation distance d, signal strength E, and resonance response intensity R is extracted from the dynamic resonance adaptation association rules, i.e., R = f(E) = f(E0 × k^d), where E0 is the signal strength at the discharge point and k is the attenuation coefficient. According to the minimum signal strength Emin required for the effective resonance response determined in step S116, when E = Emin, the corresponding resonance response intensity R reaches the effective threshold. Combining the transmission attenuation data E = E0 × k^d, d = log(E0 / Emin) / log(1 / k) can be derived, which is the maximum propagation distance corresponding to the effective resonance response. For example, if E0 = 100mV / m, Emin = 10mV / m, and k = 0.8 (20% attenuation per meter), then d = log(100 / 10) / log(1 / 0.8) = log(10) / log(1.25) ≈ 1 / 0.0969 ≈ 10.3 meters, that is, the maximum propagation distance is about 10 meters.

[0085] Step S123: Using the key parts in the three-dimensional structural model data of the switching equipment that are prone to partial discharge as the center, and the maximum propagation distance of the effective resonance response as the radius, or according to the equipment structure, a spatial range is defined as the initial resonance candidate region. The initial resonance candidate region covers the spatial location where the signal strength is not lower than the minimum signal strength required for the effective resonance response.

[0086] In this embodiment, a spherical region is defined in three-dimensional space, centered on the critical part of the switchgear prone to partial discharge (such as the circuit breaker contact coordinates (0.65m, 1.0m, 0.45m)) and with a radius of 10 meters (the maximum propagation distance calculated in step S122). However, considering the shielding effect of the switchgear's outer casing, the signal attenuation is small when propagating inside the casing, but significant after penetrating the casing. Therefore, the initial resonance candidate region needs to be adjusted in conjunction with the equipment structure. The actual defined initial resonance candidate region includes the internal space of the switchgear and the space within a 0.5-meter radius outside the casing, where the signal strength is not lower than Emin. For example, the coordinate range of the internal space of the switchgear is (0m, 0m, 0m) to (1.5m, 2.0m, 1.0m), and the external 0.5-meter range is (-0.5m, -0.5m, -0.5m) to (2.0m, 2.5m, 1.5m). The two are combined to form the initial resonance candidate region.

[0087] Step S124: Combining the resonance correction correspondence between the environment and quantum state in the dynamic resonance adaptation association rule, analyze the effects of temperature gradient, humidity distribution and electromagnetic interference source location of the operating environment of the switching equipment on the quantum state resonance stability, and eliminate areas where environmental interference exceeds the adjustment range of the resonance correction correspondence.

[0088] In this embodiment, the environmental monitoring system acquires the temperature gradient (e.g., 25 degrees Celsius on the left side of the cabinet, 30 degrees Celsius on the right), humidity distribution (60%RH at the bottom, 50%RH at the top), and the location of electromagnetic interference sources (e.g., a frequency converter 1 meter away on the right side of the cabinet, generating strong electromagnetic interference). Based on the correspondence between environment and quantum state resonance correction in the dynamic resonance adaptation association rules, when the temperature change exceeds ±10 degrees Celsius, the humidity change exceeds ±30%RH, and the electromagnetic interference intensity exceeds 60 dBμV / m, the resonance correction cannot fully compensate for the frequency shift, leading to quantum state instability. Therefore, in the initial resonance candidate region, areas with a temperature gradient exceeding 10 degrees Celsius / meter, humidity fluctuation exceeding 30%RH, and electromagnetic interference intensity exceeding 60 dBμV / m are eliminated. For example, the electromagnetic interference intensity in the outer right side of the cabinet near the frequency converter reaches 70 dBμV / m, exceeding the adjustment range, and is therefore eliminated.

[0089] Step S125: Based on the three-dimensional structural model data of the switching equipment, analyze the structural obstruction within the initial resonance candidate area, eliminate spatial areas where partial discharge signals cannot reach due to obstruction by internal components of the equipment, and retain areas where the signal propagation path is unobstructed.

[0090] In this embodiment, ray tracing analysis is performed using three-dimensional structural model data to simulate the propagation path of partial discharge signals from key locations to various points in the initial resonance candidate region. For the internal area of ​​the switchgear, the signal obstruction by components such as circuit breakers and busbars is analyzed. For example, the narrow space at the rear of the cabinet is blocked by busbars, preventing the signal from reaching it, and is therefore eliminated. For the external area, the location of openings in the cabinet shell (such as observation windows and ventilation openings) is analyzed. Signals can only propagate to the outside through these openings; therefore, only the fan-shaped area in front of the opening is retained in the external area, and the remaining areas completely blocked by the shell are eliminated. For example, if there is a 0.5m × 0.5m observation window on the front of the cabinet, the signal propagation path within a 0.5-meter radius in front of it is unobstructed and is retained.

[0091] Step S126: Obtain the spatial dimension data around the switching equipment, and remove the spatial areas from the reserved areas that cannot accommodate the physical structure of the quantum sensing unit or that hinder the normal operation and maintenance of the equipment.

[0092] In this embodiment, the spatial dimensions around the switchgear include the distance between the switchgear and the wall (0.8 meters), the distance between the switchgear and other equipment (1.0 meter), and the width of the operation and maintenance passage (1.2 meters). The physical dimensions of the quantum sensing unit are 0.2 meters long, 0.1 meters wide, and 0.15 meters high, requiring at least 0.3 meters of operating space for installation. From the area reserved in step S125, spaces smaller than the physical structure of the unit (such as narrow gaps) and areas located within the operation and maintenance passage that obstruct the opening of the switchgear door (door opening angle 90 degrees, required space range) are eliminated. For example, there is an operation passage 0.5 meters in front of the observation window on the front of the switchgear; this area needs to be reserved for maintenance. Therefore, the area within 0.3 meters in front of the observation window is considered the installation area, and the area between 0.3 meters and 0.5 meters is eliminated.

[0093] Step S127: Based on the multi-unit resonance coordination correspondence rules, the corresponding data of direction angle and resonance superposition effect in the dynamic resonance adaptation association rules, determine a set of unit spatial position combinations within the reserved area that can make the resonance response areas of each unit jointly cover the target space and the resonance interference between units is lower than the preset threshold.

[0094] In this embodiment, the target space is the critical area of ​​the switchgear prone to partial discharge, requiring at least three quantum sensing units to achieve full coverage. According to the multi-unit resonance coordination rule, the distance between adjacent units is no less than 1.5 meters or 1.0 meter with an angle of 90 degrees. Within the reserved area (e.g., 0.3 meters in front of the front observation window of the switchgear, 0.3 meters in front of the left-side ventilation opening, and the unobstructed area on the right side), three initial locations are selected: A (0.3m, 1.0m, 0.5m), B (1.8m, 1.0m, 0.5m), and C (0.9m, 2.5m, 0.5m). The distances between A and B are calculated to be 1.5 meters (meeting the minimum distance requirement), A and C 1.5 meters, and B and C 1.7 meters, all satisfying the coordination rule. Using the corresponding data of the directional angle and resonance superposition effect, the polarization directions of A, B, and C are set to 0 degrees, 90 degrees, and 180 degrees respectively, further reducing interference. This combination of locations can collectively cover the critical area, and the interference between units is below the threshold.

[0095] Step S128: Construct a quantum state resonance simulation model. Import the partial discharge signal physical attribute dataset, quantum state control component information of the quantum sensing unit, and single-unit quantum state resonance adaptation corresponding model from the dynamic resonance adaptation association rules into the partial discharge signal propagation sub-model, quantum sensing unit quantum state sub-model, and environmental interference sub-model of the quantum state resonance simulation model, respectively. Calculate the quantum state resonance response efficiency at different locations within the reserved area. The quantum state resonance response efficiency is the ratio of the resonance response intensity of the quantum sensing unit to the signal interference intensity at that location, forming the quantum state resonance response efficiency distribution data of the reserved area.

[0096] In this embodiment, the quantum state resonance simulation model is constructed using the finite element method and includes three sub-models. The partial discharge signal propagation sub-model simulates the propagation of the signal in space based on the signal's physical property dataset (frequency, polarization, attenuation), outputting the signal strength and direction at each location. The quantum state sub-model of the quantum sensing unit calculates the quantum state energy level transition frequency and polarization direction at different locations based on the control component information and the single-unit model, thereby obtaining the resonance response intensity. The environmental interference sub-model calculates the interference intensity at each location based on environmental data. The resonance response efficiency is defined as the ratio of the resonance response intensity to the interference intensity; a higher ratio indicates that the location is more suitable for sensor deployment. By setting grid points at 0.1-meter intervals within the reserved area, the resonance response efficiency of each grid point is calculated, forming efficiency distribution data; for example, the efficiency value of one grid point is 5.2, and another grid point is 3.8, etc.

[0097] Step S1281: Construct a quantum state resonance simulation model, which includes a partial discharge signal propagation sub-model, a quantum state sub-model of quantum sensing unit, an environmental interference sub-model, and a resonance response calculation sub-model.

[0098] In this embodiment, the quantum state resonance simulation model is built on the COMSOL Multiphysics software platform, employing a coupled simulation using electromagnetic field and quantum mechanics modules. The partial discharge signal propagation sub-model uses the finite-difference time-domain (FDTD) method to solve Maxwell's equations, simulating the propagation process of the electromagnetic field signal. The quantum sensing unit quantum state sub-model, based on the Schrödinger equation, simulates the quantum energy level transition process. The environmental interference sub-model transforms factors such as temperature, humidity, and electromagnetic interference into perturbation terms affecting the quantum state. The resonance response calculation sub-model calculates the response intensity and interference intensity based on the resonance matching degree between the signal and the quantum state, thereby obtaining the resonance response efficiency. Parameters are transferred between the sub-models via a data interface; for example, the signal parameters output by the signal propagation sub-model serve as the input to the quantum state sub-model, and the interference parameters output by the environmental interference sub-model simultaneously affect the quantum state sub-model.

[0099] Step S1282: Import the frequency fluctuation range, polarization direction change trajectory, and transmission attenuation data from the partial discharge signal physical attribute dataset in the dynamic resonance adaptation association rule into the partial discharge signal propagation sub-model to simulate the propagation process of the partial discharge signal in the reserved area and output the signal parameters at each location.

[0100] In this embodiment, the frequency fluctuation range of the partial discharge signal physical attribute dataset is 50MHz to 500MHz, the polarization direction change trajectory is 0 degrees to 180 degrees over time, and the transmission attenuation data is a distance attenuation coefficient k = 0.8 / m. This data is imported into the partial discharge signal propagation sub-model, with the signal source set as the coordinates of a key part within the switchgear, and the signal strength E0 = 100mV / m. Simulation calculations are performed using the FDTD method, with a time step of 1 nanosecond and a simulation duration of 10 microseconds. The model output retains parameters such as signal frequency, polarization direction, and intensity for each grid point (0.1-meter interval) within the retention area. For example, at t = 5 microseconds, the signal frequency at a certain grid point is 200MHz, the polarization direction is 30 degrees, and the intensity is 15mV / m. These parameters are stored in a three-dimensional array and used as input for subsequent sub-models.

[0101] Step S1283: Import the quantum state control component information of the quantum sensing unit and the single-unit quantum state resonance adaptation corresponding model from the dynamic resonance adaptation association rule into the quantum state sub-model of the quantum sensing unit. Combine the signal parameters at each position to simulate the quantum state distribution and energy level transition characteristics of the quantum sensing unit at different positions, and output the quantum state parameters at each position.

[0102] In this embodiment, after the quantum state control component information (laser wavelength range, power range, etc.) of the quantum sensing unit and the single-unit quantum state resonance adaptation model are imported into the quantum state sub-model, the model calculates the required quantum state control parameters (wavelength, polarization angle, etc.) based on the signal parameters (frequency, polarization direction) at each position through the single-unit model, and simulates quantum energy level transitions based on the Schrödinger equation. For example, for a position with a signal frequency of 200MHz, the model calculates a laser wavelength of 1555nm, an energy level transition frequency of 200MHz, and a polarization direction of 30 degrees. The output quantum state parameters at each position include the number of energy levels, energy level spacing, transition frequency, polarization direction, etc. For example, the quantum state parameters at a certain position are: 3 energy levels, spacing of 0.8eV and 0.9eV, transition frequencies of 200MHz and 225MHz, and polarization direction of 30 degrees.

[0103] Step S1284: Import the temperature gradient, humidity distribution, and electromagnetic interference parameters in the environmental coupling influence dataset from the dynamic resonance adaptation association rule into the environmental interference sub-model to simulate the interference process of environmental factors on the quantum state resonance response and output the interference intensity data at each location.

[0104] In this embodiment, the environmental coupling effect dataset includes a temperature gradient of 2 degrees Celsius / meter, a humidity distribution of 50%RH to 70%RH, and an electromagnetic interference intensity of 30dBμV / m to 60dBμV / m. The environmental interference sub-model converts the temperature gradient into quantum level drift (e.g., for every 10 degrees Celsius increase in temperature, the energy level transition frequency shifts by 5MHz), and the humidity distribution into a decrease in quantum state stability (e.g., for every 20% increase in humidity, the stable state index increases by 0.1). The electromagnetic interference parameters are directly superimposed on the quantum state transition signal. Through simulation calculations, the interference intensity at each location is output, defined as the percentage fluctuation in the resonant response intensity caused by the interference. For example, an interference intensity of 8% at a certain location indicates that the resonant response intensity at that location fluctuates by 8% due to environmental interference.

[0105] Step S1285: In the quantum state resonance simulation model, multiple simulation test points are uniformly set according to the three-dimensional spatial coordinates of the reserved region. Each simulation test point represents a potential installation location of the quantum sensing unit.

[0106] In this embodiment, the three-dimensional spatial coordinates of the reserved area range from (0m, 0m, 0m) to (2.0m, 2.5m, 1.5m). Within this range, simulation test points are uniformly set at 0.1-meter intervals along the X, Y, and Z axes to form a three-dimensional grid. The total number of test points is (20+1)×(25+1)×(15+1)=21×26×16=8736. The coordinates (x, y, z) of each test point are accurate to 0.01 meters, such as (0.0m, 0.0m, 0.0m), (0.1m, 0.0m, 0.0m), etc., and each test point represents a potential quantum sensing unit installation location.

[0107] Step S1286: For each simulation test point, extract the signal parameters at that location output by the partial discharge signal propagation sub-model, the quantum state parameters at that location output by the quantum sensing unit quantum state sub-model, and the interference intensity data at that location output by the environmental interference sub-model.

[0108] In this embodiment, for each simulation test point (x, y, z), the signal frequency f, polarization direction P, and signal intensity E at that coordinate are extracted from the output of the partial discharge signal propagation sub-model; the quantum state energy level transition frequency f_q, polarization resonance direction P_q, and resonance response intensity R at that location are extracted from the output of the quantum state sub-model of the quantum sensing unit; and the interference intensity I at that location is extracted from the output of the environmental interference sub-model. For example, the signal parameters of the test point (0.3m, 1.0m, 0.5m) are f=200MHz, P=30 degrees, and E=15mV / m; the quantum state parameters are f_q=200MHz, P_q=30 degrees, and R=5V; and the interference intensity I=5%. The above data are stored in association with the test point coordinates.

[0109] Step S1287: Calculate the resonance response intensity of the potential installation location by using the resonance response calculation sub-model, based on the degree of resonance correspondence between the signal parameters and quantum state parameters at the location.

[0110] In this embodiment, the resonance response calculation sub-model calculates the resonance response intensity by comparing the matching degree between signal parameters and quantum state parameters. Specifically, when the deviation between the signal frequency f and the quantum state energy level transition frequency f_q is less than 1MHz, and the deviation between the signal polarization direction P and the quantum state polarization resonance direction P_q is less than 15 degrees, the resonance condition is considered to be met, and the resonance response intensity R is the product of the signal intensity E and the quantum state sensitivity. The quantum state sensitivity is determined according to the single-unit model. For example, if the sensitivity is 0.3V / (mV / m), then when E=15mV / m, R=15×0.3=4.5V. If the frequency or polarization direction deviation exceeds the range, the resonance response intensity is reduced proportionally. For example, when the frequency deviation is 2MHz, the intensity is reduced by 20%.

[0111] Step S1288: Calculate the quantum state resonance response efficiency based on the resonance response intensity and disturbance intensity data of the potential installation location.

[0112] In this embodiment, the quantum state resonance response efficiency η is defined as the ratio of the resonance response intensity R to the interference intensity I, i.e., η = R / I. For example, if the resonance response intensity R = 5V and the interference intensity I = 5% (i.e., 0.05) at a potential installation location, then η = 5 / 0.05 = 100. The higher this ratio, the better the resonance response effect at that location and the stronger the anti-interference capability.

[0113] Step S1289: Integrate the quantum state resonance response efficiency data of all simulation test points to form the quantum state resonance response efficiency distribution data of the reserved region.

[0114] In this embodiment, the coordinates (x, y, z) of all 8736 simulation test points and their corresponding quantum state resonance response efficiencies η are organized into a three-dimensional array. The three dimensions of the array correspond to the test point indices on the X, Y, and Z axes, respectively, and the array element value is the efficiency η of that point. For example, the array element (i, j, k) corresponds to the efficiency η_ijk of the test point (x_i, y_j, z_k). Simultaneously, a three-dimensional isosurface plot and a two-dimensional slice plot of the efficiency distribution are drawn to visually demonstrate the spatial distribution of efficiency within the reserved area. For example, the efficiency values ​​in the area in front of the observation window on the front of the switch cabinet are generally higher than 200, while the efficiency values ​​in some areas on the side of the cabinet are lower than 100.

[0115] Step S129: Based on the distribution data of quantum state resonance response efficiency in the reserved region, select the spatial region with the highest quantum state resonance response efficiency from the spatial regions that meet the constraints, delineate it as the quantum resonance deployment domain, and label the three-dimensional spatial coordinate range, environmental attribute parameters, and signal propagation attribute parameters of the spatial region.

[0116] In this embodiment, the spatial region satisfying the constraints includes the reserved region selected in steps S124 to S127, and the unit layout must meet the multi-unit cooperative rule. From the quantum state resonance response efficiency distribution data of the reserved region, the continuous spatial region with the highest efficiency value is identified, for example, a region with an efficiency value greater than 250. The three-dimensional spatial coordinate range of this region is (0.2m to 0.4m, 0.9m to 1.1m, 0.4m to 0.6m), that is, the space 0.2-0.4 meters in front of the front observation window of the switch cabinet, with a height of 0.4-0.6 meters and a width of 0.9-1.1 meters. The environmental attribute parameters of this region are labeled as follows: temperature 25±1 degrees Celsius, humidity 50±5%RH, electromagnetic interference intensity 30±5dBμV / m; signal propagation attribute parameters: signal frequency 150-250MHz, polarization direction 20-40 degrees, signal strength 12-18mV / m.

[0117] Step S1210: Based on the three-dimensional spatial coordinate range, environmental attribute parameters, and signal propagation attribute parameters of the quantum resonance deployment domain, output the description information of the quantum resonance deployment domain. The description information includes the region boundary coordinates, internal signal strength distribution, environmental interference distribution, and installation and operation reach range.

[0118] In this embodiment, the description information of the quantum resonance deployment domain is output in a combination of tables and text. Region boundary coordinates: minimum X = 0.2m, maximum X = 0.4m, minimum Y = 0.9m, maximum Y = 1.1m, minimum Z = 0.4m, maximum Z = 0.6m. Internal signal strength distribution: signal strength at each point within the region is between 12-18mV / m, with an average of 15mV / m and a standard deviation of 2mV / m. Environmental interference distribution: temperature distribution is uniform, with fluctuations less than ±1 degree Celsius; humidity distribution is 50±5%RH; electromagnetic interference intensity is 30-35dBμV / m, with no obvious interference sources. Installation and operation accessibility: there is 0.5 meters of operating space in front of the region, allowing sensor installation and maintenance from the front of the switch cabinet without moving other equipment.

[0119] Step S130: By adjusting the parameters of the quantum state control component, the quantum state energy level distribution, energy level transition frequency, and polarization resonance direction of the quantum sensing unit are made to resonate with the frequency distribution, polarization direction, and transmission path of the partial discharge signal.

[0120] In this embodiment, within the quantum resonance deployment domain of the 10kV switchgear, the parameters of the quantum state control components of the selected quantum sensing unit need to be precisely adjusted to achieve resonance with the partial discharge signal. This includes adjusting the wavelength and power of the laser module to match the signal frequency, adjusting the angle of the polarization control component to match the signal polarization direction, and maintaining the stability of the quantum state through the frequency locking module and the PID module. Through a series of parameter adjustment steps, it is ensured that the quantum sensing unit can accurately capture and respond to the partial discharge signal while compensating for the effects of environmental interference.

[0121] Step S131: Extract the correspondence between frequency and energy level in the dynamic resonance adaptation association rule, and delineate the quantum state energy level transition frequency range that forms a resonance response with the frequency fluctuation range of the partial discharge signal.

[0122] In this embodiment, the correspondence between frequency and energy level is extracted from the dynamic resonance adaptation association rules. Specifically, a specific signal frequency *f* corresponds to a specific quantum state energy level interval ΔE, and consequently, a specific energy level transition frequency *f_q* = ΔE / h. The frequency fluctuation range of the partial discharge signal is 50MHz to 500MHz, therefore the quantum state energy level transition frequency range needs to cover this range. Based on the correspondence, the corresponding energy level interval range is calculated to be ΔE_min = h × 50MHz to ΔE_max = h × 500MHz. For example, h = 6.626 × 10^-34 J·s, ΔE_min at 50MHz ≈ 6.626 × 10^-34 × 50 × 10^6 ≈ 3.313 × 10^-26 J, and ΔE_max at 500MHz ≈ 3.313 × 10^-25 J. Therefore, the quantum state energy level transition frequency range is defined as 50MHz to 500MHz to cover the frequency fluctuation range of the signal.

[0123] Step S132: Obtain the output wavelength adjustment range and linewidth parameters of the quantum sensing unit laser module. Based on the corresponding data of wavelength power and energy level interval in the dynamic resonance adaptation association rule, change the energy level interval of the quantum state by adjusting the output wavelength of the laser module, so that the energy level transition frequency of the quantum state falls into the resonance frequency range.

[0124] In this embodiment, the output wavelength of the quantum sensing unit's laser module is adjustable from 1550nm to 1560nm, with a linewidth parameter of 500kHz. Based on the corresponding data of wavelength power and energy level spacing in the dynamic resonance adaptation association rules (e.g., ΔE = a × λ + b × P + c), with a fixed power P = 30mW, adjusting the wavelength λ changes the energy level spacing ΔE, thereby changing the energy level transition frequency f_q = ΔE / h. For example, when f_q = 200MHz is required, ΔE = h × 200MHz ≈ 1.325 × 10^-25 J is calculated, and the required wavelength λ = 1555nm is deduced from the corresponding data. By using the laser module's wavelength tuner, the output wavelength is precisely adjusted to 1555nm, at which point the energy level transition frequency is 200MHz, falling within the resonance frequency range of 50MHz to 500MHz.

[0125] Step S133: Adjust the output power parameters within the output power adjustment range of the laser module, and combine the corresponding data of energy level interval and quantum state stability in the dynamic resonance adaptation association rule to improve the stability of the quantum state and reduce the fluctuation amplitude of energy level transition frequency.

[0126] In this embodiment, the output power adjustment range of the laser module is 10mW to 50mW. Based on the corresponding data of energy level spacing and quantum state stability in the dynamic resonance adaptation association rules, the quantum state stability index is lower (i.e., better stability) when the power is in the range of 25mW to 35mW. In step S132, the wavelength has been adjusted to 1555nm. Now, with the wavelength fixed, the power is adjusted starting from 30mW, and the quantum state stability is tested at 25mW, 30mW, and 35mW respectively. Monitoring the fluctuation amplitude of the energy level transition frequency through the quantum state detection module reveals that the fluctuation amplitude is smallest at 30mW (±0.5MHz), ±1.0MHz at 25mW, and ±0.8MHz at 35mW. Therefore, an output power of 30mW is selected to improve the stability of the quantum state and reduce frequency fluctuations.

[0127] Step S134: Extract the correspondence between polarization direction and polarization direction in the dynamic resonance adaptation association rules, and delineate the polarization angle range that forms a resonance response with the trajectory of the partial discharge signal polarization direction change.

[0128] In this embodiment, the polarization direction of the partial discharge signal changes from 0 to 180 degrees. According to the correspondence between polarization direction and polarization direction in the dynamic resonance adaptation association rule, an effective resonance response can be generated when the deviation between the polarization resonance direction of the quantum sensing unit and the signal polarization direction is within ±15 degrees. Therefore, the polarization angle range is defined as ±15 degrees of the signal polarization direction. That is, when the signal polarization direction changes from 0 to 180 degrees, the polarization angle needs to be adjusted within the range of -15 to 195 degrees (an equivalent value of 0 to 360 degrees is used in actual adjustment). For example, when the signal polarization direction is 30 degrees, the polarization angle range is 15 to 45 degrees.

[0129] Step S135: Adjust the angle of the polarization control component of the quantum sensing unit to make the polarization resonance direction of the quantum state consistent with the signal polarization direction, thereby improving the resonance response intensity.

[0130] In this embodiment, the polarization control component of the quantum sensing unit is an electrically controlled rotating polarizer with an angle adjustment range of 0-360 degrees and an adjustment accuracy of 0.1 degrees. The polarization direction of the partial discharge signal is measured in real time using a polarization detection device; for example, the current signal polarization direction is 30 degrees. Based on the polarization angle range (15 to 45 degrees) defined in step S134, the angle of the polarization control component is adjusted to 30 degrees, making the polarization resonance direction of the quantum state completely consistent with the signal polarization direction. At this point, the response intensity is measured using a resonance signal acquisition device, revealing a 20% increase compared to when the polarization direction deviates by 15 degrees, reaching the maximum response intensity.

[0131] Step S136: Obtain the modulation frequency range and response rate of the frequency locking module, adjust the operating parameters of the frequency locking module, lock the quantum state energy level transition frequency, and suppress the resonance frequency shift caused by environmental interference.

[0132] In this embodiment, the modulation frequency range of the frequency locking module is 1kHz to 20kHz, and the response rate is 10 microseconds. To lock the quantum state energy level transition frequency at 200MHz, the reference frequency of the frequency locking module is set to 200MHz, and the modulation frequency is set to 10kHz (in the middle of the modulation frequency range). By adjusting the feedback gain of the frequency locking module, the response speed to frequency deviation is matched with the response rate. When the energy level transition frequency is detected to deviate from 200MHz, the frequency locking module generates a correction signal within 10 microseconds, adjusting the wavelength of the laser module to pull the frequency back to 200MHz. For example, when a change in ambient temperature causes a frequency deviation of +2MHz, the frequency locking module quickly generates a negative wavelength adjustment signal, increasing the wavelength by Δλ, thereby reducing the energy level transition frequency and compensating for the deviation.

[0133] Step S137: Based on the control bandwidth and adjustment accuracy of the PID module, set the control parameters of the PID module to perform feedback adjustment on the offset of the quantum state energy level transition frequency.

[0134] In this embodiment, the PID module has a control bandwidth of 16kHz and an adjustment accuracy of 0.1mV. To achieve precise control of the energy level transition frequency shift, appropriate proportional gain (P), integral time (I), and derivative time (D) parameters need to be set. According to the correspondence between environment and quantum state resonance correction in the dynamic resonance adaptation association rules, the frequency shift is mainly caused by temperature changes and has a slow variation characteristic; therefore, the integral term plays a major role. Through testing, P=2.0, I=0.5 seconds, and D=0.1 seconds were set. When a frequency shift occurs, the PID module calculates the output control voltage based on the magnitude of the deviation (current frequency - target frequency), adjusts the drive current of the laser module, and then fine-tunes the wavelength to achieve frequency correction. For example, when the frequency shift is +1MHz, the PID module increases the output control voltage by 0.5mV, increasing the wavelength by Δλ and decreasing the frequency by 1MHz.

[0135] Step S1371: Obtain the control bandwidth range, adjustment accuracy parameters, and parameter adjustment range of the PID module, and clarify the adjustable range of the proportional coefficient, integral time, and derivative time.

[0136] In this embodiment, the control bandwidth of the PID module is from 1kHz to 16kHz, and the adjustment accuracy parameter is 0.1mV, meaning the minimum adjustment of the output control voltage is 0.1mV. The parameter adjustment ranges are: the proportional coefficient P is adjustable from 0.1 to 10.0, the integral time I is adjustable from 0.1 seconds to 5.0 seconds, and the derivative time D is adjustable from 0.01 seconds to 1.0 seconds. These parameter ranges are obtained from the PID module's manual and set through the parameter configuration interface of the host computer software to ensure that the parameter adjustments are within the hardware's allowable range.

[0137] Step S1372: Analyze the minute frequency fluctuation data in the partial discharge signal physical attribute dataset in the dynamic resonance adaptation association rule, and combine the effect of environmental factors on the quantum state energy level transition frequency to determine the maximum possible offset data and offset rate of the energy level transition frequency.

[0138] In this embodiment, the data on minute frequency fluctuations in the partial discharge signal physical property dataset shows that the signal frequency fluctuates within ±1MHz of the target value, with a fluctuation period of 10 milliseconds. The effects of environmental factors (temperature, humidity, and electromagnetic interference) on the quantum state energy level transition frequency are as follows: for every 1 degree Celsius change in temperature, the frequency shifts by 0.5MHz; for every 10%RH change in humidity, the frequency shifts by 0.2MHz; and for every 10dBμV / m increase in electromagnetic interference intensity, the frequency shifts by 0.1MHz. In the switchgear operating environment, the maximum rate of temperature change is 0.1 degrees Celsius / second, the humidity is 5%RH / second, and the electromagnetic interference is 5dBμV / m / second. Therefore, the maximum possible shift in the energy level transition frequency is ±3MHz (considering all environmental factors), with a shift rate of 0.05MHz / second (temperature-dominated).

[0139] Step S1373: Establish the correspondence between the PID module control parameters and the speed and effect of energy level transition frequency correction through testing.

[0140] In this embodiment, a PID parameter testing platform was built. A signal generator simulated different frequency offsets (e.g., +2MHz, -1.5MHz, etc.). The PID control parameters were changed, and the correction time (the time from the occurrence of the offset to recovery to the target frequency within ±0.1MHz) and overshoot (the maximum deviation of the frequency from the target value during the correction process) were measured. For example, when P=1.0, I=1.0 seconds, and D=0, the correction time for a +2MHz offset was 0.5 seconds, and the overshoot was 0.3MHz; when P=2.0, I=0.5 seconds, and D=0.1 seconds, the correction time was 0.3 seconds, and the overshoot was 0.1MHz. Through multiple sets of tests, the correction speed and effect under different combinations of P, I, and D were recorded, and a corresponding relationship table was established.

[0141] Step S1374: Based on the maximum possible offset and offset rate of the energy level transition frequency, and the control bandwidth of the PID module, set the initial values ​​of the proportional coefficient, integral time, and derivative time.

[0142] In this embodiment, the maximum possible offset is ±3MHz, the offset rate is 0.05MHz / second, and the PID module control bandwidth is 16kHz. According to control theory, the proportional coefficient P mainly affects the response speed, the integral time I affects the static deviation, and the derivative time D affects the overshoot. Initially, P is set to 2.0 (medium response speed), I to 0.5 seconds (quickly eliminate static deviation), and D to 0.1 seconds (suppress overshoot). These initial values ​​are based on the correspondence in step S1373, ensuring that at the maximum offset, the correction time does not exceed 0.5 seconds and the overshoot is less than 0.2MHz.

[0143] Step S1375: Build a PID parameter calibration test system, simulate the small fluctuations in the frequency of partial discharge signal through a signal generator, monitor the shift of the energy level transition frequency of the quantum sensing unit in real time through a quantum state detection module, and output the shift monitoring data.

[0144] In this embodiment, the PID parameter correction test system consists of a signal generator, a quantum sensing unit, a quantum state detection module, a data acquisition card, and a host computer. The signal generator produces a simulated partial discharge signal (simulating a maximum offset of ±3MHz) with a frequency fluctuating between 197MHz and 203MHz, and a fluctuation period of 10 milliseconds. The quantum state detection module uses a spectrometer to monitor the energy level transition frequency in real time, with a sampling rate of 1kHz. The data acquisition card transmits the frequency data to the host computer, and the host computer software records the frequency offset change over time, forming offset monitoring data, such as a time-frequency offset curve.

[0145] Step S1376: Start the PID control module, correct the offset of the energy level transition frequency based on the set initial parameters, record the frequency offset data, correction time and frequency steady state data after correction during the correction process, and form the original correction data.

[0146] In this embodiment, the PID control module is activated to correct the simulated frequency offset based on initial parameters (P=2.0, I=0.5 seconds, D=0.1 seconds). The signal generator produces a +2MHz step offset, and the host computer software records the correction process: the frequency is 202MHz at t=0, correction begins at t=0.1 seconds, and the frequency drops to 200.1MHz (entering the ±0.1MHz range) at t=0.3 seconds, with a correction time of 0.3 seconds and an overshoot of 0.1MHz. After continuous monitoring for 10 seconds, the corrected frequency stabilizes within the range of 200±0.05MHz. The above data (time, frequency offset, correction time, and stability fluctuation) are recorded to form the original correction data.

[0147] Step S1377: Based on the original calibration data, if the calibration time exceeds the preset standard or the calibrated frequency stability data exceeds the allowable range, adjust the proportional coefficient, integral time, and derivative time according to the correspondence between the PID module control parameters and the calibration speed and effect of the energy level transition frequency. Increase the proportional coefficient to improve the calibration speed, adjust the integral time to eliminate static offset, and adjust the derivative time to suppress overshoot.

[0148] In this embodiment, the preset calibration time standard is 0.4 seconds, and the allowable stable fluctuation range is ±0.1MHz. The initial parameter calibration time is 0.3 seconds (compliant with the standard), but the stable fluctuation is ±0.05MHz (better than the standard), and the overshoot is 0.1MHz (acceptable). If the calibration time exceeds 0.6 seconds (exceeds the standard) during testing, the proportional coefficient P is increased (e.g., from 2.0 to 3.0) according to the corresponding relationship table to improve the calibration speed; if the static offset exceeds 0.2MHz (exceeds the allowable range), the integration time I is decreased (e.g., from 0.5 seconds to 0.3 seconds) to enhance the integration effect; if the overshoot exceeds 0.5MHz (too large), the derivative time D is increased (e.g., from 0.1 seconds to 0.2 seconds) to suppress the overshoot.

[0149] Step S1378: Repeat the calibration test and parameter adjustment until the calibration speed of the energy level transition frequency and the stable state data after calibration both reach the preset standard, forming the PID parameter optimization result. Based on the PID parameter optimization result, test the calibration effect under different frequency offset rates so that when the partial discharge signal frequency fluctuates rapidly, the PID module can still quickly and accurately correct the energy level transition frequency offset.

[0150] In this embodiment, after multiple tests and adjustments, the PID parameters were finally determined to be P=2.5, I=0.4 seconds, and D=0.15 seconds. At this time, the correction time for the +3MHz step offset was 0.35 seconds, the overshoot was 0.15MHz, and the stable fluctuation after correction was ±0.08MHz, all meeting the preset standards. Further testing of the correction effect at different offset rates (such as 0.1MHz / second and 0.5MHz / second) revealed that when the offset rate was 0.5MHz / second (rapid fluctuation), the PID module could still correct the frequency to the target value within ±0.1MHz within 0.4 seconds, meeting the correction requirements for the frequency fluctuation of the partial discharge signal.

[0151] Step S1379: Record the final PID module control parameters to form a parameter configuration that matches the requirements of quantum state resonance, incorporate it into the parameter configuration set of the quantum state control component, and maintain the continuous stable state of quantum state energy level transition frequency.

[0152] In this embodiment, the final PID module control parameters are: proportional coefficient P = 2.5, integral time I = 0.4 seconds, and derivative time D = 0.15 seconds. These parameters are integrated with the laser module's wavelength (1555nm), power (30mW), polarization modulation component angle (30 degrees), and frequency locking module modulation frequency (10kHz) to form a parameter configuration set for the quantum state control component. This set is stored in the control unit of the quantum sensing unit to maintain a continuous and stable quantum state energy level transition frequency.

[0153] Step S138: Extract the correspondence between signal propagation distance, signal intensity and resonance response intensity in the dynamic resonance adaptation association rules, combine the transmission attenuation data in the partial discharge signal physical attribute dataset in the dynamic resonance adaptation association rules, fine-tune the output power of the laser module and the angle of the polarization control component, compensate for the intensity attenuation during signal transmission, and maintain the resonance response effect.

[0154] In this embodiment, the relationship between signal propagation distance, signal strength, and resonant response intensity is R = 0.3 × E (where E is the signal strength in mV / m), and the transmission attenuation data is E = E0 × k^d. The quantum sensing unit is installed at a distance of d = 1.5 meters from the discharge point, E0 = 100 mV / m, k = 0.8, and the calculated E = 100 × 0.8^1.5 ≈ 100 × 0.715 = 71.5 mV / m. The theoretical resonant response intensity R = 0.3 × 71.5 ≈ 21.45 V. The actual measured response intensity is 20 V, lower than the theoretical value, indicating additional attenuation. By fine-tuning the laser module output power from 30 mW to 32 mW, the response intensity increases to 20.8 V; further fine-tuning the polarization control component angle from 30 degrees to 32 degrees further increases the response intensity to 21.3 V, close to the theoretical value. Therefore, by fine-tuning the power and polarization angle, signal transmission attenuation is compensated, maintaining the resonant response effect.

[0155] Step S139: Test the resonant response performance of the adjusted quantum sensing unit, record the resonant response intensity, response time and signal distortion data for partial discharge signals of different frequencies and polarization directions, and form a resonant response performance test dataset.

[0156] In this embodiment, the response performance of the adjusted quantum sensing unit to partial discharge signals at different frequencies (50MHz, 200MHz, 500MHz) and different polarization directions (0 degrees, 90 degrees, 180 degrees) was tested. For each frequency-polarization combination, the resonant response intensity (peak voltage), response time (time from signal occurrence to peak response), and signal distortion (waveform similarity between the output and input signals) were measured. For example, at a frequency of 200MHz and a polarization of 30 degrees, the response intensity was 21.3V, the response time was 50µs, and the distortion was 5%; at a frequency of 50MHz and a polarization of 0 degrees, the response intensity was 18V, the response time was 60µs, and the distortion was 8%. All test data were compiled into a table to form a resonant response performance test dataset.

[0157] Step S1310: Based on the resonance response performance test dataset, integrate all adjusted parameters to form a parameter configuration set for the quantum state control component, so that the quantum state energy level distribution, energy level transition frequency, polarization resonance direction of the quantum sensing unit under the parameter configuration set of the quantum state control component achieve a complete resonance correspondence with the physical properties of the partial discharge signal.

[0158] In this embodiment, parameter combinations with the highest response intensity, shortest response time, and lowest distortion at each frequency and polarization direction are selected from the resonant response performance test dataset and integrated to form a parameter configuration set for the quantum state control component. This parameter configuration set includes: laser module wavelength of 1550-1560nm (automatically adjusted according to frequency), power of 30-35mW (adjusted according to distance), polarization control component angle of 0-180 degrees (adjusted according to polarization direction), frequency locking module modulation frequency of 10kHz, and PID module parameters P=2.5, I=0.4 seconds, and D=0.15 seconds. Under this parameter configuration set, the energy level transition frequency of the quantum sensing unit covers 50-500MHz, and the polarization resonance direction covers 0-180 degrees, achieving complete resonance with the physical properties of the partial discharge signal, ensuring a stable and efficient resonant response under various signal conditions.

[0159] Step S140: Based on the corresponding data of the critical value of inter-unit resonance interference, the directional angle and the resonance superposition effect determined by the multi-unit resonance cooperative correspondence rule in the dynamic resonance adaptation association rule, determine the spatial position of each unit in the quantum sensing array, so that the resonance response area of ​​each unit jointly covers the target space, and the resonance interference between units is lower than the preset threshold.

[0160] In this embodiment, within the quantum resonance deployment domain of the 10kV switchgear, the spatial positions of three quantum sensing units need to be determined to achieve comprehensive coverage of key components within the switchgear, while ensuring that the resonance interference between units is below a preset threshold of 5%. According to the multi-unit resonance coordination rule, the minimum spacing between units is 1.5 meters or 1.0 meter (90-degree angle). By analyzing the shape of the target space and the distribution of key components, combined with the corresponding data of the directional angle and resonance superposition effect, a suitable arrangement is selected, the three-dimensional coordinates of each unit are calculated, and the interference level is verified, ultimately determining the spatial position of each unit.

[0161] Step S141: Determine the critical value of inter-unit resonance interference according to the multi-unit resonance cooperative correspondence rule in the dynamic resonance adaptation association rule, including the minimum unit spacing and / or the range of directional angles.

[0162] In this embodiment, the critical value for inter-unit resonance interference in the multi-unit resonance coordination rule is as follows: when the unit spacing is not less than 1.5 meters, the interference intensity is less than 5% regardless of the directional angle; when the unit spacing is 1.0 meter and the directional angle is 90 degrees, the interference intensity is also less than 5%. Therefore, the minimum unit spacing is determined to be 1.5 meters (any angle) or 1.0 meter (90-degree angle), and the directional angle range is preferably selected as 90 degrees to reduce the spacing requirement.

[0163] Step S142: Based on the three-dimensional spatial coordinate range of the quantum resonance deployment domain and the coverage requirements of the target space, the number of units and the arrangement of the quantum sensing array are initially planned.

[0164] In this embodiment, the three-dimensional spatial coordinate range of the quantum resonance deployment domain is (0.2m to 0.4m, 0.9m to 1.1m, 0.4m to 0.6m), and the target space is the area where key parts (circuit breaker contacts, disconnector blades, busbar joints) are located within the switchgear. To achieve full coverage, the initial plan is for three units, arranged in a triangular pattern, so that the resonant response areas of the three units overlap and cover each other.

[0165] Step S143: Combining the corresponding data of the directional angle and the resonance superposition effect, under the preliminary planned arrangement, assign polarization resonance directions to each unit to reduce resonance interference between units.

[0166] In this embodiment, the data corresponding to the directional angle and the resonance superposition effect show that the resonance superposition interference is minimized when the polarization direction angle between adjacent units is 90 degrees. Therefore, assigning polarization directions of 0 degrees, 90 degrees, and 180 degrees to the three units, such that the angle between adjacent units is 90 degrees (0 degrees and 90 degrees, 90 degrees and 180 degrees), and the angle between relative units is 180 degrees (0 degrees and 180 degrees), can effectively reduce the interference between units.

[0167] Step S144: Calculate the spatial coordinates of each element based on the critical value of inter-element resonance interference and the assigned polarization direction, ensuring that the spacing meets the critical value requirements.

[0168] In this embodiment, an equilateral triangle arrangement is adopted, and the unit spacing is set to 1.0 meter (the minimum spacing to satisfy a 90-degree angle). Taking the center of the quantum resonance deployment domain (0.3m, 1.0m, 0.5m) as the center of the triangle, the coordinates of the three units are calculated: Unit 1 (0.3-0.5×cos(30°), 1.0-0.5×sin(30°), 0.5) ≈ (0.3-0.433, 1.0-0.25, 0.5) = (-0.133m, 0.75m, 0.5m); Unit 2 (0.3+0.5× cos(30°), 1.0-0.5×sin(30°), 0.5)≈(0.3+0.433, 1.0-0.25, 0.5)=(0.733m, 0.75m, 0.5m;Unit 3(0.3, 1.0+0.5×sin(60°), 0.5)≈(0.3, 1.0+0.433, 0.5)=(0.3m, 1.433m, 0.5m)。Check the spacing: Unit 1-2 spacing ≈ 1.0 meter, Unit 1-3 spacing ≈ 1.0 meter, Unit 2-3 spacing ≈ 1.0 meter, which meets the critical value requirements.

[0169] Step S145: Verify whether the resonance response regions of each element jointly cover the target space. If there is a coverage blind spot, adjust the element coordinates or increase the number of elements.

[0170] In this embodiment, the resonant response region of each quantum sensing unit is a sphere with a radius of 10 meters centered at its coordinates (determined based on the maximum propagation distance). The coordinates of the key locations in the target space are (0.65m, 1.0m, 0.45m), (0.8m, 0.9m, 0.5m), and (0.5m, 1.1m, 0.55m). Inspection revealed that the response regions of all three units cover all key locations without any blind spots. Therefore, there is no need to adjust the coordinates or increase the number of units.

[0171] Step S146: Calculate the resonance interference intensity between units. If there is a unit group whose interference intensity exceeds the preset threshold, adjust the unit coordinates or polarization direction until the interference intensity between all units is lower than the preset threshold.

[0172] In this embodiment, the preset interference intensity threshold is 5%. The interference intensity between unit 1 (0 degrees) and unit 2 (90 degrees) is calculated as follows: with a distance of 1.0 meter and an angle of 90 degrees, the interference intensity is 3% (below the threshold) based on the corresponding data of the directional angle and the resonance superposition effect; the interference intensity between unit 2 (90 degrees) and unit 3 (180 degrees) is 3%; the interference intensity between unit 1 (0 degrees) and unit 3 (180 degrees) with a distance of 1.0 meter and an angle of 180 degrees is 4% (below the threshold). The interference intensity between all units is below 5%, which meets the requirements. Therefore, the spatial positions of each unit are determined as unit 1 (-0.133m, 0.75m, 0.5m), unit 2 (0.733m, 0.75m, 0.5m), and unit 3 (0.3m, 1.433m, 0.5m).

[0173] Step S150: Through dynamic iterative quantum resonance testing, continuously optimize the spatial position and quantum state control parameters of each unit to form an optimized layout scheme for the partial discharge quantum sensing array. The optimized layout scheme includes quantum state resonance adaptation parameters, unit spatial resonance coordinates, quantum state control component parameter configuration, and resonance operation and maintenance requirements.

[0174] In this embodiment, after determining the initial spatial position and quantum state control parameters of each unit in the quantum sensing array, it is necessary to verify the actual operating effect through dynamic iterative testing and optimize and adjust according to the test results. This process includes building a test platform, simulating partial discharge signals, collecting response data, analyzing problematic units, adjusting parameters and positions, and repeating the test until all performance indicators meet the standards, ultimately forming an optimized deployment scheme containing detailed parameters and maintenance requirements.

[0175] Step S151: Construct a partial discharge signal simulation generator within the quantum resonance deployment domain. This partial discharge signal simulation generator generates a partial discharge signal that is consistent with the actual operation of the switching equipment, simulating the frequency fluctuation, polarization change, and transmission attenuation characteristics of the signal.

[0176] In this embodiment, the partial discharge signal simulation device consists of a high-voltage pulse generator, an adjustable frequency signal source, a polarization controller, and an attenuator. The high-voltage pulse generator produces pulse signals, and the frequency, amplitude, and other characteristics can be controlled by adjusting parameters. By adjusting the frequency and phase of the signal source, the frequency fluctuations (50-500MHz) and polarization changes (0-180 degrees) of the actual partial discharge signal are simulated. The attenuator is set with an attenuation coefficient according to the transmission distance, simulating the signal attenuation during spatial propagation (k=0.8 / meter). The device is installed near critical parts of the switchgear where partial discharge is prone to occur, ensuring that the propagation path of the simulated signal is consistent with the actual situation.

[0177] Step S152: Based on the determined spatial location and parameter configuration set of the quantum state control component, install all units of the quantum sensing array and connect the quantum state control circuit, signal acquisition circuit and data transmission system.

[0178] In this embodiment, three quantum sensing units are installed within the quantum resonance deployment domain according to the unit spatial coordinates determined in step S146. Each unit is fixed by a dedicated bracket, and its height and angle are adjusted to ensure its coordinates are accurate to ±0.01 meters. The quantum state control circuit connects the laser module, frequency locking module, PID module, and polarization control component, and its parameters are set by a unified control unit. The signal acquisition circuit transmits the resonance response signals of each unit to the data acquisition card, with the sampling rate set to 1MHz. The data transmission system uses Ethernet to send the acquired data to the host computer for analysis, ensuring that the data transmission delay is less than 100 milliseconds.

[0179] Step S153: Start the partial discharge signal simulation generator to make the partial discharge signal spread in the quantum resonance deployment domain according to the actual propagation law, and at the same time start the quantum state control system of the quantum sensing array to make each unit enter the resonance response state.

[0180] In this embodiment, a partial discharge signal simulation generator is activated, with a signal frequency of 200MHz, a polarization direction of 30 degrees, an initial intensity of 100mV / m, and continuous output for 10 minutes. Simultaneously, the quantum state control system of the quantum sensing array is activated, loading the parameter configuration set. Each unit automatically adjusts parameters such as laser wavelength, power, and polarization angle to enter a resonant response state. The quantum state detection module monitors the quantum state energy level transition frequency and polarization direction in real time to ensure that each unit is in a resonant state.

[0181] Step S154: Record the resonance response data of each quantum sensing unit through the data acquisition system, including resonance response intensity, energy level transition frequency steady state data, polarization resonance matching data, response delay time and inter-unit resonance interference data, to form the original resonance response dataset.

[0182] In this embodiment, the data acquisition system continuously collects the response data of each unit for 10 minutes, recording once every 100 milliseconds. The resonant response intensity is the peak voltage of the signal (in V); the steady-state data of the energy level transition frequency is the frequency fluctuation range (in MHz); the polarization resonance matching data is the deviation between the actual polarization direction and the signal polarization direction (in degrees); the response delay time is the time from signal occurrence to the peak response (in microseconds); and the inter-unit resonance interference data is the cross-correlation coefficient (dimensionless) of the response signals of adjacent units. For example, unit 1 has a response intensity of 21V, a frequency fluctuation of ±0.5MHz, a polarization deviation of 2 degrees, a response delay of 45 microseconds, and a cross-correlation coefficient of 0.03 with unit 2 (interference intensity 3%). All data are integrated to form the original resonant response dataset.

[0183] Step S155: Based on the original resonance response dataset, analyze the resonance response performance of each unit, screen units whose resonance response intensity does not meet the preset standard, units whose energy level transition frequency steady state data exceeds the allowable range, and unit groups whose inter-unit resonance interference data exceeds the allowable range, and form a list of problematic units / groups.

[0184] In this embodiment, the preset standards are: resonant response intensity not lower than 18V, energy level transition frequency fluctuation not exceeding ±1MHz, polarization deviation not exceeding ±15 degrees, response delay not exceeding 100 microseconds, and inter-unit cross-correlation coefficient (interference intensity) not exceeding 0.05 (5%). Analysis of the original resonant response dataset revealed that unit 3's response intensity was 17V (lower than 18V), and its energy level transition frequency fluctuation was ±1.2MHz (exceeding ±1MHz); the cross-correlation coefficient between unit 1 and unit 3 was 0.06 (6%, exceeding 5%). Therefore, the list of problematic units includes unit 3 (intensity and frequency stability issues), and the list of problematic unit groups includes units 1 and 3 (interference issues).

[0185] Step S1551: Construct a resonance response performance evaluation index, which includes a resonance response intensity evaluation value, an energy level transition frequency steady state evaluation value, and a resonance interference degree evaluation value.

[0186] In this embodiment, the resonant response performance evaluation indicators include: resonant response intensity evaluation value R (unit V, directly using the measured peak voltage); energy level transition frequency steady state evaluation value F (unit MHz, the difference between the maximum and minimum values ​​of frequency fluctuation within a preset time); and resonant interference degree evaluation value I (dimensionless, the cross-correlation coefficient of the response signals of adjacent units, the larger the value, the more severe the interference).

[0187] Step S1552: Set quantitative standards for each evaluation index, and mark the qualified range of resonance response intensity, the qualified range of stable state of energy level transition frequency, and the allowable range of resonance interference degree.

[0188] In this embodiment, the quantitative standards for each evaluation index are as follows: the qualified range of resonance response intensity [18V, 30V] (below 18V is unqualified, above 30V may be saturated); the qualified range of stable state of energy level transition frequency [0MHz, 1MHz] (fluctuation greater than 1MHz is unqualified); the allowable range of resonance interference degree [0, 0.05] (cross-correlation coefficient greater than 0.05 is unqualified).

[0189] Step S1553: Import the resonance response data of each quantum sensing unit into the resonance response performance evaluation index, calculate the resonance response intensity evaluation value of each unit, compare it with the qualified range, and select the units whose evaluation values ​​are lower than the lower limit of the qualified range as units whose resonance response intensity does not meet the preset standard.

[0190] In this embodiment, the resonance response intensity data of each unit is imported into the evaluation index. Unit 1 is 21V (within [18, 30], which is acceptable), Unit 2 is 22V (acceptable), and Unit 3 is 17V (below 18V, which is unacceptable). Therefore, Unit 3 is selected as the unit whose resonance response intensity does not meet the preset standard.

[0191] Step S1554: Calculate the stable state evaluation value of the energy level transition frequency for each unit. The stable state evaluation value of the energy level transition frequency is the quantification result of the fluctuation amplitude of the energy level transition frequency within a preset time. Compare it with the qualified range and select the units whose evaluation values ​​exceed the upper limit of the qualified range as units whose stable state data of the energy level transition frequency exceeds the allowable range.

[0192] In this embodiment, the preset time is 1 minute, and the frequency fluctuation amplitude of each unit within 1 minute is calculated: Unit 1 fluctuates by 0.5MHz (within [0, 1], which is acceptable), Unit 2 fluctuates by 0.6MHz (acceptable), and Unit 3 fluctuates by 1.2MHz (exceeding 1MHz, which is unacceptable). Therefore, Unit 3 is selected as the unit whose energy level transition frequency stable state data exceeds the allowable range.

[0193] Step S1555: Calculate the resonance interference level assessment value between adjacent units. The resonance interference level assessment value is the superposition interference quantization result of the resonance response signals of two units. Compare it with the allowable range and select the unit combination whose assessment value exceeds the upper limit of the allowable range as the unit group whose inter-unit resonance interference data exceeds the allowable range.

[0194] In this embodiment, the cross-correlation coefficient of the response signals of adjacent units is calculated: 0.03 for unit 1 and unit 2 (within [0, 0.05], acceptable), 0.04 for unit 2 and unit 3 (acceptable), and 0.06 for unit 1 and unit 3 (exceeding 0.05, unacceptable). Therefore, unit 1 and unit 3 are selected as the unit group whose inter-unit resonance interference data exceeds the allowable range.

[0195] Step S1556: Based on the list of units whose resonance response intensity does not meet the preset standard, analyze the relationship between their installation location and the propagation path of the partial discharge signal, and record the obstruction situation and signal intensity distribution on the signal propagation path.

[0196] In this embodiment, the installation position of unit 3, whose resonant response intensity did not meet the standard, was (0.3m, 1.433m, 0.5m). Analysis of its propagation path with the signal source (circuit breaker contact coordinates (0.65m, 1.0m, 0.45m)) revealed that a metal beam from the switchgear obstructed the path, leading to increased signal attenuation. The actual signal intensity at unit 3 was measured to be 65mV / m (theoretical value 71.5mV / m), lower than expected, resulting in insufficient response intensity. The obstruction details (metal beam, 5mm thickness, position (0.3m, 1.2m, 0.5m)) and signal intensity distribution (65mV / m at unit 3, 70-72mV / m at other units) were recorded.

[0197] Step S1557: Based on the list of units whose stable state data of energy level transition frequencies exceed the allowable range, analyze the parameter configuration of their quantum state control components, and record the correlation data between the parameter settings of the laser module, frequency locking module, and PID module and environmental interference.

[0198] In this embodiment, the quantum state control component parameters of unit 3, where the energy level transition frequency stability state exceeds the limit, are as follows: laser wavelength 1555nm, power 30mW, frequency locking modulation frequency 10kHz, and PID parameters P=2.5, I=0.4 seconds, and D=0.15 seconds. Analysis of environmental interference data revealed that the temperature fluctuation at unit 3 was ±2 degrees Celsius (compared to ±1 degree Celsius for other units), leading to increased frequency fluctuation. The correlation between parameter settings and environmental interference was recorded: a 2-degree Celsius temperature fluctuation corresponds to a 1.2MHz frequency fluctuation, which the PID module failed to fully compensate for.

[0199] Step S1558: Based on the list of unit groups whose inter-unit resonance interference data exceeds the allowable range, and combined with the corresponding data of the directional angle and resonance superposition effect in the dynamic resonance adaptation association rules, analyze their spatial position relationship and polarization resonance direction, record the data on the effect of unit spacing and directional angle on the degree of interference, integrate the analysis results, establish analysis reports for problem units and problem unit groups, and record the manifestation, data support and cause data of each problem.

[0200] In this embodiment, the distance between unit 1 (0 degrees) and unit 3 (180 degrees) is 1.0 meter, and the directional angle is 180 degrees. According to the data corresponding to the directional angle and resonance superposition effect in the dynamic resonance adaptation association rules, the interference intensity is 4% at a 180-degree angle, but the actual measurement is 6%. Analysis of the spatial relationship reveals that unit 3 is offset by 0.1 meters towards unit 1 due to obstruction, resulting in an actual distance of 0.9 meters and increased interference. Recorded data: interference intensity of 6% at a distance of 0.9 meters and a 180-degree angle. The analysis report indicates that the insufficient response intensity of unit 3 is due to signal obstruction; the frequency instability is due to large temperature fluctuations; and the excessive interference between units 1 and 3 is due to the small distance between them.

[0201] Step S1559: Based on the analysis report, output the list of problem units, the list of problem unit groups, and the corresponding analysis report.

[0202] In this embodiment, the output problem unit list is as follows: Unit 3 (resonance response intensity 17V<18V, frequency fluctuation 1.2MHz>1MHz); the problem unit group list is as follows: Unit 1 and Unit 3 (cross-correlation coefficient 0.06>0.05). The analysis report describes in detail the manifestation of each problem (low intensity, large frequency fluctuation, excessive interference), data support (comparison of measured values ​​and standard values), and causes (signal obstruction, temperature fluctuation, insufficient spacing).

[0203] Step S156: Based on the list of problem units / groups, for units whose resonant response intensity is lower than the preset standard, adjust the parameters of their quantum state control components according to the correspondence between signal propagation distance and signal intensity and resonant response intensity in the dynamic resonance adaptation association rules, and adjust their spatial position to the coordinate point with higher partial discharge signal intensity.

[0204] In this embodiment, to address the low response intensity of unit 3, based on the correspondence between signal strength and resonant response intensity R=0.3×E, the signal intensity E needs to be increased. The spatial position of unit 3 is adjusted from (0.3m, 1.433m, 0.5m) to (0.3m, 1.3m, 0.5m) (moving 0.133m towards the signal source) to avoid obstruction by the metal beam. After adjustment, the measured signal intensity E=75mV / m (higher than the previous 65mV / m). Simultaneously, the power of the fine-tuned laser module is increased from 30mW to 33mW. According to the correspondence R=0.3×75=22.5V, the expected response intensity will increase to 22.5V.

[0205] Step S157: Based on the list of problem units / groups, for units whose stable state data of energy level transition frequencies exceeds the allowable range, optimize the parameter configuration of the frequency locking module and the PID module, combine the corresponding data of energy level interval and quantum state stable state in the dynamic resonance adaptation association rules to enhance the stability of the quantum state, and at the same time adjust the installation and fixing method to reduce the effect of mechanical vibration on the quantum state.

[0206] In this embodiment, to address the issue of large frequency fluctuations in unit 3, the modulation frequency of the frequency-locking module was increased from 10kHz to 15kHz to improve response speed; the PID parameters were optimized to P=3.0 (enhancing proportional action) and I=0.3 seconds (enhancing integral action). Based on the corresponding data of energy level spacing and quantum state stability, the laser wavelength was fine-tuned to 1555.5nm, slightly increasing the energy level spacing and improving stability. Simultaneously, the mounting bracket for unit 3 was replaced with a vibration-damping bracket to reduce the impact of mechanical vibration on the quantum state.

[0207] Step S158: Based on the list of problematic units / groups, for unit groups where the inter-unit resonance interference data exceeds the allowable range, according to the multi-unit resonance synergy correspondence rules in the dynamic resonance adaptation association rules, the corresponding data of the direction angle and resonance superposition effect, increase the spatial spacing between units, or adjust the polarization resonance direction of one of the units, so that the inter-unit resonance interference is reduced to the allowable range.

[0208] In this embodiment, to address the issue of excessive interference between unit 1 and unit 3, the polarization resonance direction of unit 3 is adjusted from 180 degrees to 90 degrees (90 degrees angle with unit 1). According to the corresponding data of the direction angle and the resonance superposition effect, the interference intensity can be reduced to 3% at a 90-degree angle. At the same time, the new positions of unit 3 (0.3m, 1.3m, 0.5m) are maintained, with a distance of 1.0 meter from unit 1, satisfying the critical condition of 1.0 meter distance + 90-degree angle.

[0209] Step S159: Restart the partial discharge signal simulation generator and quantum sensing array, collect the resonance response data of each unit after optimization, form a resonance response optimization dataset, compare the differences between the original resonance response dataset and the resonance response optimization dataset, and continue the adjustment and testing process until the resonance response performance data of all units reach the preset standard, and the overall resonance coverage of the array has no blind spots and the resonance interference between units is lower than the preset threshold. Record the final spatial resonance coordinates of each unit, the parameter configuration of the quantum state control component, and the resonance operation and maintenance requirements to form an optimized deployment scheme.

[0210] In this embodiment, the test system was restarted, and optimized data was collected: the response intensity of unit 3 was 22V (meeting the standard), and the frequency fluctuation was 0.8MHz (meeting the standard); the cross-correlation coefficient between unit 1 and unit 3 was 0.03 (meeting the standard). All unit performance indicators met the standards, and there were no blind spots in the coverage. The final parameters were recorded: the unit spatial resonance coordinates were unit 1 (-0.133m, 0.75m, 0.5m), unit 2 (0.733m, 0.75m, 0.5m), and unit 3 (0.3m, 1.3m, 0.5m); the quantum state control component parameter configuration included the wavelength, power, polarization angle, frequency locking, and PID parameters of each unit; the resonance operation and maintenance requirements included regular (monthly) calibration of the laser wavelength and polarization direction, quarterly checks of the frequency locking module and PID module parameters, and annual replacement of the vibration damping bracket, etc. Integrating this information, an optimized deployment scheme for the partial discharge quantum sensing array was formed.

[0211] In one exemplary embodiment, a partial discharge quantum sensing array optimization deployment system is provided. This system can be a terminal, server, etc., and its internal structure diagram can be as follows: Figure 2As shown, the partial discharge quantum sensing array optimization deployment system includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides the environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, near-field communication, or other technologies. When the computer program is executed by the processor, it implements a partial discharge quantum sensing array optimization deployment method. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device can be a touch layer covering the display screen, or a button, trackball, or touchpad set on the housing of the partial discharge quantum sensing array optimization deployment system, or an external keyboard, touchpad, or mouse, etc.

[0212] It should be noted that, in order to simplify the description of the present invention and thus help to understand one or more embodiments of the invention, multiple features may sometimes be grouped into one embodiment, drawing or description thereof in the foregoing description of the embodiments of the present invention.

Claims

1. A method for optimizing the layout of a partial discharge quantum sensing array, characterized in that, The method includes: A dynamic resonance adaptation association rule is established between the partial discharge signal of the switching device and the quantum state of the quantum sensing unit. The dynamic resonance adaptation association rule adjusts parameters to make the quantum state energy level of the quantum sensing unit resonate with the physical properties of the partial discharge signal. Based on the dynamic resonance adaptation association rule, the quantum resonance deployment domain of the quantum sensing array is locked. The quantum resonance deployment domain is the spatial range in which the partial discharge signal excites the quantum sensing unit to generate a stable resonance response and the environmental interference has the least effect on the resonance response. By adjusting the parameters of the quantum state control component, the quantum state energy level distribution, energy level transition frequency, and polarization resonance direction of the quantum sensing unit can resonate with the frequency distribution, polarization direction, and transmission path of the partial discharge signal. Based on the multi-unit resonance cooperative correspondence rule in the dynamic resonance adaptation association rule, the corresponding data of the critical value of resonance interference between units, the direction angle and the resonance superposition effect are determined, and the spatial position of each unit in the quantum sensing array is determined so that the resonance response area of ​​each unit jointly covers the target space and the resonance interference between units is lower than the preset threshold. Through dynamic iterative testing of quantum resonance, the spatial position and quantum state control parameters of each unit are continuously optimized to form an optimized layout scheme for the partial discharge quantum sensing array. The optimized layout scheme includes quantum state resonance adaptation parameters, unit spatial resonance coordinates, quantum state control component parameter configuration, and resonance operation and maintenance requirements.

2. The method for optimizing the layout of a partial discharge quantum sensing array according to claim 1, characterized in that, The establishment of dynamic resonance adaptation correlation rules between the partial discharge signal of the switching device and the quantum state of the quantum sensing unit includes: A partial discharge signal is generated by applying voltage to the switching device under different insulation conditions. The partial discharge signal is collected and the occurrence time of the partial discharge signal, the time difference of the partial discharge signal reaching the sensor at different spatial locations, and the signal strength measured at each spatial location are recorded to form a partial discharge signal physical attribute dataset. The quantum state control component information of the quantum sensing unit is obtained. The quantum state control component information of the quantum sensing unit includes the output wavelength range, output power adjustment range, and linewidth parameters of the laser module, the modulation frequency range and response rate of the frequency locking module, the control bandwidth and adjustment accuracy of the PID module, and the angle adjustment range and response sensitivity parameters of the polarization control component. The quantum state energy level distribution of the quantum sensing unit under different quantum state control parameters was tested. By adjusting the output wavelength and power of the laser module, the energy level spacing of the quantum inside the quantum sensing unit was changed. The quantum state stable state data corresponding to different energy level spacing were recorded, forming the corresponding data of wavelength power and energy level spacing, and the corresponding data of energy level spacing and quantum state stable state. The frequency range in the physical property dataset of partial discharge signal is compared with the quantum state energy level transition frequency. Based on the corresponding data of wavelength power and energy level interval, the output wavelength of the laser module is adjusted to change the quantum state energy level transition frequency. The range of energy level transition frequencies that can make the quantum sensing unit resonate with the partial discharge signal is determined, and the correspondence between frequency and energy level is established. The polarization direction in the partial discharge signal physical property dataset is compared with the polarization resonance direction of the quantum sensing unit. The angle of the polarization control component is adjusted to change the polarization resonance direction of the quantum state. The range of polarization angles that can make the quantum sensing unit resonate with the partial discharge signal is determined, and the correspondence between the polarization direction and the polarization direction is established. By extracting transmission attenuation data from the partial discharge signal physical property dataset and combining it with the corresponding data of energy level spacing and quantum state stability, the change of quantum state resonance response intensity with signal propagation distance is analyzed. The minimum intensity of partial discharge signal required for the quantum sensing unit to generate an effective resonance response is determined, and the correspondence between signal propagation distance, signal intensity and resonance response intensity is established. Collect temperature, humidity, and electromagnetic interference data of the operating environment of the switching equipment, record the offset data of quantum state energy level transition frequency under different environmental conditions, and establish the resonance correction correspondence between the environment and the quantum state; Based on the correspondence between frequency and energy level, the correspondence between polarization direction and polarization direction, the correspondence between signal propagation distance and signal intensity and resonance response intensity, and the resonance correction correspondence between environment and quantum state, a single-unit quantum state resonance adaptation correspondence model is constructed. The single-unit quantum state resonance adaptation correspondence model describes the resonance interaction mode between a single quantum sensing unit and the partial discharge signal. Based on the single-unit quantum state resonance adaptation model, a resonance signal superposition model is introduced when multiple quantum sensing units work simultaneously. By testing, mutual interference data of quantum state resonance between adjacent units is obtained, and the minimum allowable unit spacing and / or polarization direction angle range when the resonance interference between units is lower than a preset threshold is determined, and multi-unit resonance cooperative correspondence rules are established. By integrating the physical property dataset of partial discharge signals, the quantum state modulation component information of quantum sensing units, the single-unit quantum state resonance adaptation correspondence model, and the multi-unit resonance cooperative correspondence rules, dynamic resonance adaptation association rules are formed, and a structured representation of the corresponding data including resonance correspondence parameters, resonance adjustment threshold, resonance cooperative constraint values, direction angle and resonance superposition effect is output.

3. The method for optimizing the layout of a partial discharge quantum sensing array according to claim 1, characterized in that, The process of locking the quantum resonance deployment domain of the quantum sensing array based on the dynamic resonance adaptation association rule includes: Obtain the three-dimensional structural model data of the switchgear. The three-dimensional structural model data of the switchgear includes the spatial position of the internal components, the electromagnetic conductivity coefficient of the component materials, the shielding parameters of the external shell, and the coordinates of key parts that are prone to partial discharge. Extract the correspondence between signal propagation distance, signal intensity, and resonance response intensity in the dynamic resonance adaptation association rules, define the minimum partial discharge signal intensity required for the quantum sensing unit to generate an effective resonance response, and combine the transmission attenuation data in the partial discharge signal physical attribute dataset in the dynamic resonance adaptation association rules to calculate the maximum propagation distance corresponding to the effective resonance response. Taking the key parts in the three-dimensional structural model data of the switching equipment that are prone to partial discharge as the center, and the maximum propagation distance of the effective resonance response as the radius or the spatial range defined according to the equipment structure, as the initial resonance candidate region, the initial resonance candidate region covers the spatial location where the signal strength is not lower than the minimum signal strength required for the effective resonance response. By combining the resonance correction correspondence between the environment and quantum state in the dynamic resonance adaptation association rule, we analyze the effects of temperature gradient, humidity distribution and electromagnetic interference source location of the operating environment of the switching equipment on the quantum state resonance stability, and eliminate the region where the environmental interference exceeds the adjustment range of the resonance correction correspondence. Based on the three-dimensional structural model data of the switching equipment, the structural obstruction in the initial resonance candidate area is analyzed. Spatial areas where partial discharge signals cannot reach due to obstruction by internal components of the equipment are eliminated, while areas with unobstructed signal propagation paths are retained. Obtain spatial dimension data around the switching equipment, and eliminate spatial areas from the reserved area that cannot accommodate the physical structure of the quantum sensing unit or that hinder the normal operation and maintenance of the equipment; Based on the multi-unit resonance coordination correspondence rules, the corresponding data of direction angle and resonance superposition effect in the dynamic resonance adaptation association rules, a set of unit space position combinations that can make the resonance response areas of each unit jointly cover the target space and the resonance interference between units is lower than the preset threshold are determined within the reserved area. A quantum state resonance simulation model is constructed. The partial discharge signal physical attribute dataset, quantum state control component information of quantum sensing unit, and single-unit quantum state resonance adaptation corresponding model in the dynamic resonance adaptation association rules are respectively imported into the partial discharge signal propagation sub-model, quantum sensing unit quantum state sub-model, and environmental interference sub-model of the quantum state resonance simulation model. The quantum state resonance response efficiency at different locations in the reserved area is calculated. The quantum state resonance response efficiency is the ratio of the resonance response intensity of the quantum sensing unit to the partial discharge signal to the signal interference intensity at that location, forming the quantum state resonance response efficiency distribution data of the reserved area. Based on the distribution data of quantum state resonance response efficiency in the reserved region, the spatial region with the highest quantum state resonance response efficiency is selected from the spatial regions that meet the constraints and delineated as the quantum resonance deployment domain. The three-dimensional spatial coordinate range, environmental attribute parameters and signal propagation attribute parameters of this spatial region are marked. Based on the three-dimensional spatial coordinate range, environmental attribute parameters, and signal propagation attribute parameters of the quantum resonance deployment domain, the descriptive information of the quantum resonance deployment domain is output. The descriptive information includes the region boundary coordinates, internal signal strength distribution, environmental interference distribution, and installation and operation reach range.

4. The method for optimizing the layout of a partial discharge quantum sensing array according to claim 1, characterized in that, The method of adjusting the parameters of the quantum state control component to achieve a resonant correspondence between the quantum state energy level distribution, energy level transition frequency, and polarization resonance direction of the quantum sensing unit and the frequency distribution, polarization direction, and transmission path of the partial discharge signal includes: Extract the correspondence between frequency and energy level in the dynamic resonance adaptation association rules, and delineate the quantum state energy level transition frequency range that forms a resonance response with the frequency fluctuation range of the partial discharge signal. The output wavelength adjustment range and linewidth parameters of the quantum sensing unit laser module are obtained. Based on the corresponding data of wavelength power and energy level spacing in the dynamic resonance adaptation association rule, the energy level spacing of the quantum state is changed by adjusting the output wavelength of the laser module, so that the energy level transition frequency of the quantum state falls into the resonance frequency range. Within the output power adjustment range of the laser module, the output power parameters are adjusted, and the corresponding data of energy level spacing and quantum state stability in the dynamic resonance adaptation association rule are combined to improve the stability of the quantum state and reduce the fluctuation amplitude of energy level transition frequency. Extract the correspondence between polarization direction and polarization direction in the dynamic resonance adaptation association rules, and delineate the polarization angle range that forms the resonance response with the polarization direction change trajectory of the partial discharge signal; Adjusting the angle of the polarization control component of the quantum sensing unit makes the polarization resonance direction of the quantum state consistent with the polarization direction of the signal, thereby improving the resonance response intensity; Obtain the modulation frequency range and response rate of the frequency locking module, adjust the operating parameters of the frequency locking module, lock the quantum state energy level transition frequency, and suppress the resonance frequency shift caused by environmental interference; Based on the control bandwidth and adjustment accuracy of the PID module, the control parameters of the PID module are set to provide feedback adjustment for the shift in the quantum state energy level transition frequency. The correspondence between signal propagation distance, signal intensity, and resonance response intensity in the dynamic resonance adaptation association rules is extracted. Combined with the transmission attenuation data in the partial discharge signal physical attribute dataset in the dynamic resonance adaptation association rules, the output power of the laser module and the angle of the polarization control component are finely adjusted to compensate for the intensity attenuation during signal transmission and maintain the resonance response effect. The resonant response performance of the adjusted quantum sensing unit was tested, and the resonant response intensity, response time and signal distortion data for partial discharge signals of different frequencies and polarization directions were recorded to form a resonant response performance test dataset. Based on the resonance response performance test dataset, all adjusted parameters are integrated to form a parameter configuration set for the quantum state control component, so that the quantum state energy level distribution, energy level transition frequency, polarization resonance direction of the quantum sensing unit under the parameter configuration set of the quantum state control component achieve a complete resonance correspondence with the physical properties of the partial discharge signal.

5. The method for optimizing the layout of a partial discharge quantum sensing array according to claim 1, characterized in that, The process of continuously optimizing the spatial position and quantum state control parameters of each unit through dynamic iterative quantum resonance testing includes: A partial discharge signal simulation generator is built in the quantum resonance deployment domain. This partial discharge signal simulation generator generates a partial discharge signal that is consistent with the actual operation of the switching equipment, simulating the frequency fluctuation, polarization change and transmission attenuation characteristics of the signal. Based on the determined spatial location and parameter configuration set of the quantum state control components, install all units of the quantum sensing array and connect the quantum state control circuit, signal acquisition circuit and data transmission system; The partial discharge signal simulation generator is activated to allow the partial discharge signal to propagate in the quantum resonance deployment domain according to the actual propagation law. At the same time, the quantum state control system of the quantum sensing array is activated to make each unit enter the resonant response state. The resonance response data of each quantum sensing unit is recorded by the data acquisition system, including resonance response intensity, energy level transition frequency steady state data, polarization resonance matching data, response delay time and inter-unit resonance interference data, forming the original resonance response dataset. Based on the original dataset of resonance response, the resonance response performance of each unit is analyzed, and units whose resonance response intensity does not meet the preset standard, units whose energy level transition frequency steady state data exceeds the allowable range, and unit groups whose inter-unit resonance interference data exceeds the allowable range are screened to form a list of problematic units / groups. Based on the list of problem units / groups, for units whose resonant response intensity is lower than the preset standard, the parameters of their quantum state control components are adjusted according to the correspondence between signal propagation distance and signal intensity and resonant response intensity in the dynamic resonant adaptation association rules, and their spatial position is adjusted to the coordinate point with higher partial discharge signal intensity. Based on the list of problem units / groups, for units where the stable state data of energy level transition frequencies exceeds the allowable range, the parameter configuration of the frequency locking module and PID module is optimized. Combined with the corresponding data of energy level interval and quantum state stable state in the dynamic resonance adaptation association rules, the quantum state stability is enhanced. At the same time, the installation and fixing method is adjusted to reduce the effect of mechanical vibration on the quantum state. Based on the list of problematic units / groups, for unit groups where the inter-unit resonance interference data exceeds the allowable range, according to the multi-unit resonance synergy correspondence rules in the dynamic resonance adaptation association rules, the corresponding data of the direction angle and resonance superposition effect, the spatial spacing between units is increased, or the polarization resonance direction of one of the units is adjusted, so that the inter-unit resonance interference is reduced to the allowable range. The partial discharge signal simulation generator and quantum sensing array are restarted to collect the optimized resonance response data of each unit, forming a resonance response optimization dataset. The differences between the original resonance response dataset and the optimized resonance response dataset are compared, and the adjustment and testing process continues until the resonance response performance data of all units reach the preset standard, and the overall resonance coverage of the array is without blind spots and the resonance interference between units is lower than the preset threshold. The final spatial resonance coordinates of each unit, the parameter configuration of the quantum state control component, and the resonance operation and maintenance requirements are recorded to form an optimized deployment scheme.

6. The method for optimizing the layout of a partial discharge quantum sensing array according to claim 2, characterized in that, The quantum state energy level distribution of the quantum sensing unit under different quantum state modulation parameters is tested. By adjusting the output wavelength and power of the laser module, the energy level spacing of the quanta inside the quantum sensing unit is changed, and the stable state data of the quantum state corresponding to different energy level spacings are recorded, forming corresponding data of wavelength power and energy level spacing, and corresponding data of energy level spacing and stable state of quantum state, including: A quantum state testing platform was constructed, which includes a quantum sensing unit fixing device, a laser module parameter adjustment module, a quantum state detection module, a data recording module, and an environmental control module. The quantum sensing unit is fixed in a standard position on the quantum state testing platform, and the temperature and humidity of the testing environment are adjusted by the environmental control module to keep it within the environmental conditions for normal operation of the switching equipment. The output wavelength of the laser module is adjusted by the laser module parameter adjustment module. Multiple wavelength test points are selected sequentially from the minimum adjustment range to the maximum adjustment range, and each wavelength test point corresponds to a set of energy level intervals. For each wavelength test point, the output power of the laser module is adjusted, and multiple power test points are selected sequentially from the minimum output power to the maximum output power to form multiple sets of quantum state control parameter combinations; The quantum state detection module is activated to detect the energy level distribution of quanta inside the quantum sensing unit under each combination of quantum state control parameters, and to record the number of energy levels, the energy value of each energy level and the size of the energy level interval, thus forming the raw data of energy level distribution. Based on the original energy level distribution data, the stable state of the quantum state under each set of parameters is continuously detected, and the fluctuation data of the energy level interval, the drift data of the energy level value and the quantum state holding time are recorded within a preset time to form the original data of the stable state. Based on the original data of the stable state, the stable state index of the quantum state under each set of parameters is calculated. The stable state index is a comprehensive quantitative result of the fluctuation data of the energy level interval and the drift data of the energy level value. Based on the original data of energy level distribution, the original data of steady state, and the steady state index, a table of correspondence between the combination of quantum state control parameters, the quantum state energy level distribution, and the steady state index is established. Based on the correspondence table, the correlation data between the output wavelength, output power and energy level spacing of the laser module are extracted to form the correspondence data between wavelength power and energy level spacing; Based on the correspondence table, the correlation data between energy level intervals and stable state indices are extracted to form the correspondence data between energy level intervals and quantum state stable states.

7. The method for optimizing the layout of a partial discharge quantum sensing array according to claim 3, characterized in that, The quantum state resonance response efficiency at different locations within the retention area is calculated using a quantum state resonance simulation model. The quantum state resonance response efficiency is the ratio of the resonance response intensity of the quantum sensing unit to the signal interference intensity at that location, forming quantum state resonance response efficiency distribution data for the retention area, including: A quantum state resonance simulation model is constructed, which includes a partial discharge signal propagation sub-model, a quantum state sub-model of quantum sensing unit, an environmental interference sub-model, and a resonance response calculation sub-model. The frequency fluctuation range, polarization direction change trajectory, and transmission attenuation data from the partial discharge signal physical attribute dataset in the dynamic resonance adaptation association rule are imported into the partial discharge signal propagation sub-model to simulate the propagation process of the partial discharge signal in the preserved area and output the signal parameters at each location. The quantum state control component information of the quantum sensing unit and the single-unit quantum state resonance adaptation corresponding model in the dynamic resonance adaptation association rule are imported into the quantum state sub-model of the quantum sensing unit. Combined with the signal parameters at each position, the quantum state distribution and energy level transition characteristics of the quantum sensing unit at different positions are simulated, and the quantum state parameters at each position are output. The temperature gradient, humidity distribution, and electromagnetic interference parameters in the environmental coupling influence dataset from the dynamic resonance adaptation association rule are imported into the environmental interference sub-model to simulate the interference process of environmental factors on the quantum state resonance response and output the interference intensity data at each location. In the quantum state resonance simulation model, multiple simulation test points are uniformly set according to the three-dimensional spatial coordinates of the reserved region, and each simulation test point represents the potential installation location of the quantum sensing unit. For each simulation test point, the signal parameters at that location output by the partial discharge signal propagation sub-model, the quantum state parameters at that location output by the quantum sensing unit quantum state sub-model, and the interference intensity data at that location output by the environmental interference sub-model are extracted. By using a resonant response calculation sub-model, the resonant response intensity of the potential installation location is calculated based on the degree of resonance correspondence between the signal parameters and quantum state parameters at that location. Based on the resonant response intensity and disturbance intensity data of this potential installation location, the quantum state resonant response efficiency is calculated; The quantum state resonance response efficiency data of all simulation test points are integrated to form the quantum state resonance response efficiency distribution data of the reserved region.

8. The method for optimizing the layout of a partial discharge quantum sensing array according to claim 4, characterized in that, The control bandwidth and adjustment accuracy based on the PID module, adjusting the control parameters of the PID module, and real-time correction of small shifts in the quantum state energy level transition frequency include: Obtain the control bandwidth range, adjustment accuracy parameters, and parameter adjustment range of the PID module, and clarify the adjustable range of the proportional coefficient, integral time, and derivative time; By analyzing the minute frequency fluctuations in the physical property dataset of partial discharge signals in the dynamic resonance adaptation association rules, and combining the effect of environmental factors on the quantum state energy level transition frequency, the maximum possible shift data and shift rate of the energy level transition frequency are determined. The correlation between the PID module control parameters and the speed and effect of energy level transition frequency correction was established through testing. Based on the maximum possible offset and offset rate of the energy level transition frequency, and the control bandwidth of the PID module, set the initial values ​​of the proportional coefficient, integral time, and derivative time. A PID parameter calibration test system was built. A signal generator was used to simulate the small fluctuations in the frequency of partial discharge signals. A quantum state detection module was used to monitor the shift of the energy level transition frequency of the quantum sensing unit in real time and output the shift monitoring data. The PID control module is started to correct the offset of the energy level transition frequency based on the set initial parameters. The frequency offset data, correction time and frequency steady state data after correction are recorded during the correction process to form the original correction data. Based on the original calibration data, if the calibration time exceeds the preset standard or the calibrated frequency stability data exceeds the allowable range, the proportional coefficient, integral time, and derivative time are adjusted according to the correspondence between the PID module control parameters and the calibration speed and effect of the energy level transition frequency. Increasing the proportional coefficient improves the calibration speed, adjusting the integral time eliminates static offset, and adjusting the derivative time suppresses overshoot. Repeatedly perform calibration tests and parameter adjustments until the calibration speed of the energy level transition frequency and the stable state data after calibration both reach the preset standards, forming PID parameter optimization results. Based on the PID parameter optimization results, test the calibration effect under different frequency offset rates so that when the partial discharge signal frequency fluctuates rapidly, the PID module can still quickly and accurately correct the energy level transition frequency offset. Record the final PID module control parameters to form a parameter configuration that matches the requirements of quantum state resonance, incorporate it into the parameter configuration set of the quantum state control component, and maintain the continuous stability of the quantum state energy level transition frequency.

9. The method for optimizing the layout of a partial discharge quantum sensing array according to claim 5, characterized in that, The analysis of the resonance response data of each unit filters out units whose resonance response intensity does not meet the preset standard, units whose energy level transition frequency stable state data exceeds the allowable range, and unit groups whose inter-unit resonance interference data exceeds the allowable range, including: A resonant response performance evaluation index is constructed, which includes the resonant response intensity evaluation value, the energy level transition frequency steady state evaluation value, and the resonant interference degree evaluation value. Quantitative standards are set for each evaluation index, and the acceptable ranges for resonance response intensity, energy level transition frequency stability, and resonance interference degree are marked. The resonance response data of each quantum sensing unit is imported into the resonance response performance evaluation index. The resonance response intensity evaluation value of each unit is calculated and compared with the qualified range. Units whose evaluation values ​​are lower than the lower limit of the qualified range are selected as units whose resonance response intensity does not meet the preset standard. Calculate the stable state evaluation value of the energy level transition frequency for each unit. The stable state evaluation value of the energy level transition frequency is the quantification result of the fluctuation amplitude of the energy level transition frequency within a preset time. Compare it with the qualified range and select the units whose evaluation values ​​exceed the upper limit of the qualified range as units whose stable state data of energy level transition frequency exceeds the allowable range. Calculate the resonance interference level assessment value between adjacent units. The resonance interference level assessment value is the superposition interference quantization result of the resonance response signals of the two units. Compare it with the allowable range and select the unit combination whose assessment value exceeds the upper limit of the allowable range as the unit group whose inter-unit resonance interference data exceeds the allowable range. Based on the list of units whose resonant response intensity did not meet the preset standard, the relationship between their installation location and the propagation path of partial discharge signal was analyzed, and the obstruction and signal intensity distribution on the signal propagation path were recorded. Based on the list of units whose steady-state data of energy level transition frequencies exceed the allowable range, analyze the parameter configuration of their quantum state control components, and record the correlation data between the parameter settings of the laser module, frequency locking module, and PID module and environmental interference. Based on the list of unit groups whose inter-unit resonance interference data exceeds the allowable range, and combined with the corresponding data of the directional angle and resonance superposition effect in the dynamic resonance adaptation association rules, we analyze their spatial position relationship and polarization resonance direction, record the data on the effect of unit spacing and directional angle on the degree of interference, integrate the analysis results, establish analysis reports for problem units and problem unit groups, and record the manifestation, data support and cause data of each problem. Based on the analysis report, output a list of problem units, a list of problem unit groups, and the corresponding analysis report.

10. A partial discharge quantum sensing array optimized deployment system, characterized in that, include: processor; A machine-readable storage medium for storing machine-executable instructions of the processor; The processor is configured to execute the partial discharge quantum sensing array optimization deployment method according to any one of claims 1 to 9 by executing the machine-executable instructions.

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