A solid-state smart circuit breaker control method

Abstract

The application relates to the technical field of circuit breaker control, in particular to a solid intelligent circuit breaker control method.The method comprises the following steps: monitoring and processing the circuit breaker through a sensor to obtain circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, circuit breaker load data and circuit breaker communication data; performing state matrix design and electrical parameter correction processing of the circuit breaker according to the circuit breaker radio frequency data, the circuit breaker electrical parameter data, the circuit breaker thermal energy data, the circuit breaker load data and the circuit breaker communication data to generate corrected circuit breaker state matrix data; performing frequency band impedance change calculation of the circuit breaker electrical parameter and cooperative control analysis of the circuit breaker on the corrected circuit breaker state matrix data, and performing on-off operation on the circuit breaker. Through comprehensive analysis of multi-source power condition information data, the application realizes intelligent coordinated control of the power network.

Description

Technical Field

[0001] This invention relates to the field of circuit breaker control technology, and in particular to a solid-state digital intelligent circuit breaker control method. Background Technology

[0002] With the development trend of intelligent power distribution networks and intelligent power electronic devices, power distribution systems have placed higher demands on circuit breakers for intelligent, refined, and collaborative control. Solid-state intelligent circuit breakers, as a new type of breaking device integrating electronic devices and digital control technologies, can further improve the safety, reliability, and efficiency of power grid operation through their level of intelligence. However, current circuit breaker control methods generally rely on preset rules and electrical parameter judgment strategies for breaking operations. In application scenarios such as distributed energy access, dynamic changes in power load, and frequent switching of complex operating conditions, circuit breakers struggle to comprehensively regulate themselves based on multi-source power state information such as radio frequency characteristics, thermal distribution, and load changes. The circuit breaker control methods lack the ability to coordinate control over the entire power network, leading to misjudgments in circuit breaker operating status identification and abnormal control parameter configurations. Summary of the Invention

[0003] Based on this, the present invention provides a solid-state intelligent circuit breaker control method to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, a solid-state intelligent circuit breaker control method includes the following steps:

[0005] Step S1: Monitor the circuit breaker using sensors to obtain circuit breaker monitoring data, which includes circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, circuit breaker load data, and circuit breaker connection data; design the circuit breaker state matrix based on the circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, and circuit breaker load data to generate circuit breaker state matrix data;

[0006] Step S2: Analyze the on / off changes of the circuit breaker based on the circuit breaker load data and circuit breaker connection data to generate on / off change data; perform electrical parameter correction processing on the circuit breaker state matrix data based on the on / off change data to generate corrected circuit breaker state matrix data.

[0007] Step S3: Based on the circuit breaker radio frequency data, circuit breaker electrical parameter data, and circuit breaker thermal energy data, calculate the frequency band impedance change of the circuit breaker electrical parameters on the modified circuit breaker state matrix data to generate circuit breaker frequency band impedance data.

[0008] Step S4: Based on the circuit breaker frequency band impedance data, perform parameter coordination configuration of the circuit breaker to generate circuit breaker parameter coordination configuration data;

[0009] Step S5: Obtain real-time power demand data; perform coordinated circuit breaker control analysis on the corrected circuit breaker state matrix data based on the real-time power demand data and circuit breaker parameter coordination configuration data to generate coordinated circuit breaker control data; perform on / off operations on the circuit breaker based on the coordinated circuit breaker control data.

[0010] Furthermore, step S1 includes the following steps:

[0011] Step S11: The circuit breaker is monitored and processed by the sensor to obtain circuit breaker monitoring data, wherein the circuit breaker monitoring data includes circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, circuit breaker load data and circuit breaker connection data.

[0012] Step S12: Obtain circuit breaker design structure data, and perform unit topology analysis on circuit breaker connection data based on circuit breaker design structure data to generate circuit breaker unit topology data; perform time synchronization processing on circuit breaker unit topology data to generate time-synchronized circuit breaker unit topology data.

[0013] Step S13: Perform spatial hierarchy design of the circuit breaker based on the time-synchronous circuit breaker unit topology data, and generate circuit breaker spatial hierarchy data;

[0014] Step S14: Based on the circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, and circuit breaker load data, design the state matrix of the circuit breaker spatial hierarchy data to generate the circuit breaker state matrix data.

[0015] Furthermore, step S2 includes the following steps:

[0016] Step S21: Based on the circuit breaker load data, perform load link analysis on the circuit breaker to generate load link data;

[0017] Step S22: Detect the status of the circuit breaker's interactive nodes based on the circuit breaker connection data, and generate interactive node status data;

[0018] Step S23: Based on the interactive node status data, perform circuit breaker on / off loop reconstruction processing on the load link data to generate on / off loop reconstruction data;

[0019] Step S24: Analyze the on / off changes of the circuit breaker based on the on / off circuit reconstruction data, and generate on / off change data;

[0020] Step S25: Based on the on / off change data, perform a transmission link stability assessment on the on / off circuit reconstruction data of the circuit breaker to generate transmission link stability assessment data;

[0021] Step S26: Based on the transmission link stability assessment data, perform electrical parameter correction processing on the circuit breaker state matrix data to generate corrected circuit breaker state matrix data.

[0022] Furthermore, step S3 includes the following steps:

[0023] Step S31: Extract the radio frequency characteristics of the circuit breaker based on the circuit breaker radio frequency data to generate radio frequency characteristic data;

[0024] Step S32: Perform electrical-composite frequency band analysis on the circuit breaker based on radio frequency characteristic data and circuit breaker electrical parameter data to generate electrical-composite frequency band data;

[0025] Step S33: Perform thermal-electric spectrum correlation mapping processing on the circuit breaker based on the circuit breaker thermal energy data and electrical-composite frequency band data to generate thermal-electric spectrum correlation data;

[0026] Step S34: Based on the thermal-electric spectrum correlation data, perform frequency band impedance change analysis on the corrected circuit breaker state matrix data to generate circuit breaker frequency band impedance data.

[0027] Furthermore, step S32 includes the following steps:

[0028] Step S321: Based on the radio frequency characteristic data and the circuit breaker electrical parameter data, perform current transmission fluctuation analysis of the circuit breaker to generate current transmission fluctuation data;

[0029] Step S322: Perform electrical-radio frequency coupling resonance mapping of the circuit breaker based on the current transmission fluctuation data to generate electrical-radio frequency coupling resonance data;

[0030] Step S323: Perform electrical-composite frequency band analysis on the circuit breaker based on the electrical-RF coupling resonance data to generate electrical-composite frequency band data.

[0031] Furthermore, step S321 includes the following steps:

[0032] RF frequency strength is calculated based on RF characteristic data to generate RF frequency strength data.

[0033] Based on radio frequency intensity data, the deviation of current transmission impact of circuit breakers is evaluated, and current transmission impact deviation data is generated.

[0034] The current resonant frequency is extracted based on the circuit breaker's electrical parameter data to generate current resonant frequency data.

[0035] The current transmission amount of the circuit breaker is calculated based on the current resonant frequency data, and the current transmission amount data is generated.

[0036] Based on the deviation data of current transmission influence, the current transmission fluctuation of the circuit breaker is analyzed using the current transmission quantity data, and current transmission fluctuation data is generated.

[0037] Furthermore, step S33 includes the following steps:

[0038] Step S331: Perform thermal energy fluctuation analysis on the circuit breaker based on the circuit breaker thermal energy data, and generate thermal energy fluctuation data;

[0039] Step S332: Based on thermal energy fluctuation data, perform voltage fluctuation analysis on electrical-composite frequency band data of the circuit breaker to generate voltage fluctuation data;

[0040] Step S333: Analyze the voltage response frequency of the circuit breaker based on the voltage fluctuation data to generate voltage response frequency data;

[0041] Step S334: Perform thermo-electric spectrum correlation mapping processing based on voltage response frequency data and electrical-composite frequency band data to generate thermo-electric spectrum correlation data.

[0042] Furthermore, step S34 includes the following steps:

[0043] Step S341: Analyze the abnormal tripping control attribute status of the circuit breaker based on the thermal-electric spectrum correlation data, and generate abnormal tripping control attribute status data;

[0044] Step S342: Perform timing on / off matrix analysis of the circuit breaker based on the abnormal disconnection attribute status data, and generate timing on / off matrix data;

[0045] Step S343: Based on the timing on / off matrix data, perform frequency band impedance change analysis on the corrected circuit breaker state matrix data to generate circuit breaker frequency band impedance data.

[0046] Furthermore, step S4 includes the following steps:

[0047] Step S41: Perform frequency band division processing on the circuit breaker frequency band impedance data to generate circuit breaker frequency band impedance data.

[0048] Step S42: Analyze the frequency band impedance response characteristics based on the circuit breaker frequency band impedance data to generate frequency band impedance response characteristic data.

[0049] Step S43: Calculate the frequency band impedance fluctuation of the circuit breaker based on the frequency band impedance response characteristic data, and generate frequency band impedance fluctuation data;

[0050] Step S44: Analyze the circuit breaker's tripping delay deviation based on the frequency band impedance fluctuation data, and generate tripping delay deviation data;

[0051] Step S45: Analyze the control of the circuit breaker's linkage nodes based on the control delay deviation data, and generate linkage node control data;

[0052] Step S46: Calculate the electrical node parameters of the circuit breaker based on the linkage node control data, and generate electrical node parameter data;

[0053] Step S47: Based on the electrical node parameter data and the linkage node control data, perform parameter coordination configuration of the circuit breaker to generate circuit breaker parameter coordination configuration data.

[0054] Furthermore, step S5 includes the following steps:

[0055] Step S51: Obtain real-time power demand data, calculate the demand impact range of the real-time power demand data, and generate demand impact range data;

[0056] Step S52: Based on the demand impact range data, sort the real-time power demand data to generate sorted real-time power demand data;

[0057] Step S53: Based on the sorted real-time power demand data, perform coordinated circuit breaker parameter configuration on the circuit breaker to generate coordinated circuit breaker control data, and perform on / off operations on the circuit breaker through the coordinated circuit breaker control data.

[0058] The beneficial effects of this invention are:

[0059] This invention proposes a solid-state intelligent circuit breaker control method. It utilizes multi-dimensional sensors to monitor and process circuit breaker radio frequency data, electrical parameter data, thermal energy data, load data, and connection data, providing a comprehensive understanding of the circuit breaker's operating status from various perspectives. Based on the monitoring data, a state matrix is ​​designed to generate state matrix data, systematically integrating the monitoring data to present the overall operating status of the circuit breaker in a structured form. This facilitates accurate understanding of the circuit breaker's operation and lays a solid foundation for intelligent management and optimized operation. On / off change analysis is performed using load and connection data. Load data assesses the stress load on mechanical components during operation, determining the presence of wear and fatigue. Connection data directly reflects the circuit breaker's connection status, confirming the effectiveness of on / off operations and monitoring the conduction status of various currents. Electrical parameter correction processing is applied to the circuit breaker state matrix data based on on / off change data, dynamically adjusting and correcting electrical parameters in the state matrix based on conventional operating conditions according to actual on / off conditions. Based on circuit breaker radio frequency data, circuit breaker electrical parameter data, and circuit breaker thermal energy data, the frequency band impedance change of the circuit breaker's electrical parameters is calculated using the corrected circuit breaker state matrix data. The frequency band impedance change of the circuit breaker directly reflects the changes in its internal electrical performance. Radio frequency signals are used to assist in analyzing the causes of impedance anomalies, electrical parameters directly participate in impedance calculations, and thermal energy data verifies the correlation between impedance changes and local overheating. Based on the changing trends of the frequency band impedance data, corresponding maintenance measures can be taken in advance to avoid the occurrence and expansion of faults, improving the reliability of circuit breaker on / off control. Parameter coordination configuration of the circuit breaker is performed based on the circuit breaker's frequency band impedance data. The various parameters of the circuit breaker are interconnected and influence each other. Reasonable parameter configuration is crucial for ensuring the stable operation of the circuit breaker and optimizing power system performance. Parameter coordination configuration based on the circuit breaker's frequency band impedance data allows for targeted adjustments and optimizations of its electrical and mechanical parameters according to the current operating state of the circuit breaker. This enables the circuit breaker to maintain its optimal operating state under different working environments and load conditions, improving its adaptability to complex operating conditions. By integrating real-time power demand and parameter coordination configuration data for collaborative circuit breaker control analysis, real-time demand data reflects the dynamics of the power grid load, while parameter configuration data provides the optimal operating parameters for the circuit breaker. The combination of these two factors enables precise matching of switching operations with power demand. Through multi-objective optimization, collaborative circuit breaker control commands are generated to drive the circuit breaker to perform switching operations. Comprehensive analysis of multi-source information data achieves intelligent control of the circuit breaker.

[0060] The solid-state intelligent circuit breaker control method of the present invention is applied to scenarios such as distributed energy access, dynamic changes in power load, and frequent switching of complex operating conditions. At the same time, it performs comprehensive regulation of the circuit breaker based on multi-source power status information such as the circuit breaker's radio frequency characteristics, thermal energy distribution, and load changes, reducing misjudgments in circuit breaker operation status identification and abnormal control parameter configuration, thereby realizing the ability to coordinate control of the entire power network. Attached Figure Description

[0061] Figure 1 This is a schematic diagram of the steps of the solid-state intelligent circuit breaker control method of the present invention;

[0062] Figure 2 for Figure 1 A detailed flowchart illustrating the implementation steps of step S1.

[0063] Figure 3 for Figure 1 A detailed flowchart illustrating the implementation steps of step S2.

[0064] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0065] The technical method of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this invention.

[0066] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0067] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0068] To achieve the above objectives, please refer to Figures 1 to 3 This invention provides a solid-state intelligent circuit breaker control method, comprising the following steps:

[0069] Step S1: Monitor the circuit breaker using sensors to obtain circuit breaker monitoring data, which includes circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, circuit breaker load data, and circuit breaker connection data; design the circuit breaker state matrix based on the circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, and circuit breaker load data to generate circuit breaker state matrix data;

[0070] Step S2: Analyze the on / off changes of the circuit breaker based on the circuit breaker load data and circuit breaker connection data to generate on / off change data; perform electrical parameter correction processing on the circuit breaker state matrix data based on the on / off change data to generate corrected circuit breaker state matrix data.

[0071] Step S3: Based on the circuit breaker radio frequency data, circuit breaker electrical parameter data, and circuit breaker thermal energy data, calculate the frequency band impedance change of the circuit breaker electrical parameters on the modified circuit breaker state matrix data to generate circuit breaker frequency band impedance data.

[0072] Step S4: Based on the circuit breaker frequency band impedance data, perform parameter coordination configuration of the circuit breaker to generate circuit breaker parameter coordination configuration data;

[0073] Step S5: Obtain real-time power demand data; perform coordinated circuit breaker control analysis on the corrected circuit breaker state matrix data based on the real-time power demand data and circuit breaker parameter coordination configuration data to generate coordinated circuit breaker control data; perform on / off operations on the circuit breaker based on the coordinated circuit breaker control data.

[0074] In the embodiments of this invention, please refer to Figure 1 The diagram shown is a flowchart illustrating the steps of the solid-state intelligent circuit breaker control method of the present invention. In this example, the solid-state intelligent circuit breaker control method includes the following steps:

[0075] Step S1: Monitor the circuit breaker using sensors to obtain circuit breaker monitoring data, which includes circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, circuit breaker load data, and circuit breaker connection data; design the circuit breaker state matrix based on the circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, and circuit breaker load data to generate circuit breaker state matrix data;

[0076] In this embodiment of the invention, a high-precision sensor array is used to monitor the circuit breaker. Specifically, a microwave radio frequency sensor, operating in the 2.4 GHz band, is used to collect radio frequency data of the circuit breaker, acquiring the intensity and phase information of the radio frequency reflected signal from the circuit breaker contacts and connections every 100 milliseconds. Hall effect current sensors and voltage transformers are used to collect electrical parameters of the circuit breaker, obtaining parameters such as current, voltage, and power factor 10 times per second. An infrared thermal imager is used to collect thermal energy data of the circuit breaker at a frequency of 5 frames per second, obtaining a surface temperature distribution map of the equipment. A combination of pressure and displacement sensors is used to collect circuit breaker load data, monitoring changes in contact pressure and mechanical displacement in real time. Fiber optic sensors are used to monitor the circuit breaker's connection data, accurately determining the closed and open states of the contacts. The collected circuit breaker radio frequency (RF) data, electrical parameter data, thermal data, and load data are preprocessed. RF signals are filtered and denoised, with a median filtering algorithm used to remove outliers. Electrical parameters are normalized, mapping current, voltage, and other parameters to the 0-1 range. Thermal data undergoes temperature threshold analysis to identify abnormal temperature regions. Then, according to pre-defined matrix construction rules, each type of data is filled into a multi-dimensional matrix to form the circuit breaker state matrix data. For example, the first row of the matrix represents the time series, and the remaining rows correspond to data such as RF signal strength, current, voltage, and temperature. Each column represents a different monitoring point or parameter category, ultimately generating a state matrix data containing comprehensive operational status information of the circuit breaker.

[0077] Step S2: Analyze the on / off changes of the circuit breaker based on the circuit breaker load data and circuit breaker connection data to generate on / off change data; perform electrical parameter correction processing on the circuit breaker state matrix data based on the on / off change data to generate corrected circuit breaker state matrix data.

[0078] In this embodiment of the invention, by analyzing the contact pressure data change curve collected by the pressure sensor, when the pressure drops by more than a set threshold (e.g., 30% of the initial pressure) within 100 milliseconds, and the fiber optic sensor detects an increase in the contact gap exceeding 0.1 mm, the circuit breaker is determined to have disconnected; conversely, if the pressure rises and the contact gap recovers, it is determined to have closed. These on / off change information are recorded as time-state sequence data, forming on / off change data. Electrical parameters are corrected based on the on / off change data in the circuit breaker state matrix. For example, if a closing operation is found to be unsuccessful, and the state matrix shows an abnormally low current value, a regression model I established using historical data is used. 修正= a×U+b, where a and b are coefficients obtained by fitting historical normal operation data, and U is the voltage value measured by the voltage sensor. The current value is recalculated and corrected, thereby correcting the electrical parameter data in the entire state matrix. When the circuit breaker is detected to be open, the current parameter at the corresponding time point in the state matrix is ​​forcibly set to 0. At the same time, the equivalent no-load impedance value is calculated based on the voltage and power factor before the opening, and the relevant parameters in the matrix are updated. When the circuit breaker is closed, the electrical parameters in the state matrix are dynamically corrected based on the voltage and current surge data at the moment of closing. A linear interpolation algorithm is used to smooth the transition parameter changes and generate corrected circuit breaker state matrix data to ensure that the matrix data can accurately reflect the operating state after the circuit breaker's on / off changes.

[0079] Step S3: Based on the circuit breaker radio frequency data, circuit breaker electrical parameter data, and circuit breaker thermal energy data, calculate the frequency band impedance change of the circuit breaker electrical parameters on the modified circuit breaker state matrix data to generate circuit breaker frequency band impedance data.

[0080] In this embodiment of the invention, a Fast Fourier Transform (FFT) is performed on the acquired circuit breaker radio frequency data to convert the time-domain signal into a frequency-domain signal, obtaining the radio frequency signal strength S at different frequencies. Combined with the voltage and current values ​​in the circuit breaker's electrical parameter data, the complex impedance calculation formula is used. U and I represent voltage and current in complex form, respectively. The complex impedance Z is calculated as Z = Re(Z) + j × Im(Z), where Re(Z) is the real part of the complex impedance, j is the imaginary unit representing the reactance due to the phase difference between current and voltage, and Im(Z) is the imaginary part of the complex impedance, yielding impedance values ​​for different frequency bands. To comprehensively consider the influence of the real and imaginary parts of the complex impedance, as well as the radio frequency signal strength, on the frequency band impedance, the real and imaginary parts of the complex impedance are weighted by the radio frequency signal strength at the corresponding frequency. The weights are derived from historical fault data. Combining the voltage and current spectral distribution in the electrical parameter data, a Fourier transform is used to convert the time-domain signal to a frequency-domain signal, obtaining the voltage, current amplitude, and phase difference for each frequency band. For example, with a real part weight of 0.6, an imaginary part weight of 0.4, and a radio frequency signal strength weight of 0.2, the frequency band impedance calculation formula is constructed: Z 频段= 0.6×Re(Z) + 0.4×Im(Z) + 0.2×S, where 0.6×Re(Z) represents the proportion of influence assigned to the real part of the complex impedance. The real part typically reflects the magnitude of the resistance of resistive elements in the circuit to current. In historical fault data, abnormal changes in the real part are associated with many fault conditions. 0.4×j represents the influence of the imaginary part of the complex impedance. The imaginary part is related to energy storage elements such as capacitors and inductors in the circuit, and its changes also have a significant impact on the electrical performance of the circuit breaker. S represents the radio frequency signal strength at the corresponding frequency. 0.2×S incorporates the effect of the radio frequency signal strength. The radio frequency signal strength generated by partial discharge can reflect potential problems such as internal insulation of the circuit breaker. Including it with appropriate weights can make the calculated Z... 频段 This provides a more comprehensive reflection of the actual impedance characteristics of the circuit breaker at different frequency bands, thereby obtaining the impedance values ​​for each frequency band. Simultaneously, based on the circuit breaker's thermal energy data, the frequency band impedance values ​​are corrected using the thermal-impedance relationship model ΔZ = α × ΔT (where α is the temperature coefficient of the material and ΔT is the temperature change).

[0081] Step S4: Based on the circuit breaker frequency band impedance data, perform parameter coordination configuration of the circuit breaker to generate circuit breaker parameter coordination configuration data;

[0082] In this embodiment of the invention, a mapping table between frequency band impedance and circuit breaker control parameters is established. For example, when the impedance value of the 2.4GHz frequency band is between 8Ω and 12Ω, the overcurrent protection threshold of the circuit breaker is set to 1.2 times the rated current; when the impedance value is greater than 12Ω, the overcurrent protection threshold is reduced to 1.1 times the rated current. Based on the circuit breaker frequency band impedance data, the mapping table is consulted to coordinate the configuration of the circuit breaker's protection parameters (such as overcurrent protection threshold and leakage current operating current) and control parameters (such as contact operating time and opening / closing speed). Simultaneously, considering the impact of impedance changes in different frequency bands on system stability, when abnormal fluctuations occur in the impedance of multiple frequency bands, a multi-objective optimization algorithm is used to dynamically adjust the values ​​of each parameter while ensuring protection reliability and system stability. The finally determined parameter configuration information is recorded as a parameter-value data table, generating circuit breaker parameter coordination configuration data.

[0083] Step S5: Obtain real-time power demand data; perform coordinated circuit breaker control analysis on the corrected circuit breaker state matrix data based on the real-time power demand data and circuit breaker parameter coordination configuration data to generate coordinated circuit breaker control data; perform on / off operations on the circuit breaker based on the coordinated circuit breaker control data.

[0084] In this embodiment of the invention, real-time power demand data, including active power, reactive power, and apparent power, is collected by a smart meter on a minute-by-minute basis. The real-time power demand data is compared and analyzed with the corrected circuit breaker state matrix data. When the real-time active power exceeds 80% of the circuit breaker's rated power, and the frequency band impedance data indicates overload risk in some frequency bands, a collaborative disconnection analysis is initiated. Based on the protection thresholds and control parameters in the circuit breaker parameter coordination configuration data, and combined with the real-time power demand and the current state of the circuit breaker, a decision tree algorithm is used to make on / off decisions. For example, if the current exceeds the current protection threshold and the duration exceeds 5 seconds, while the circuit breaker is in a closed state, it is determined that a disconnection operation needs to be performed; if the real-time power demand decreases and the system stability meets the requirements, closing the circuit breaker is considered to restore power supply. The decision results are recorded as operation-time series data to generate collaborative disconnection data. Finally, the coordinated disconnection control data is transmitted to the circuit breaker's actuator via a hard-wired connection or wireless communication module (such as a communication module based on the ZigBee protocol, operating in the 2.4GHz band), driving the circuit breaker's electromagnetic or permanent magnet operating mechanism to perform on / off operations according to the instructions in the coordinated disconnection control data, thereby achieving precise control of the solid-state intelligent circuit breaker.

[0085] Furthermore, step S1 includes the following steps:

[0086] Step S11: The circuit breaker is monitored and processed by the sensor to obtain circuit breaker monitoring data, wherein the circuit breaker monitoring data includes circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, circuit breaker load data and circuit breaker connection data.

[0087] Step S12: Obtain circuit breaker design structure data, and perform unit topology analysis on circuit breaker connection data based on circuit breaker design structure data to generate circuit breaker unit topology data; perform time synchronization processing on circuit breaker unit topology data to generate time-synchronized circuit breaker unit topology data.

[0088] Step S13: Perform spatial hierarchy design of the circuit breaker based on the time-synchronous circuit breaker unit topology data, and generate circuit breaker spatial hierarchy data;

[0089] Step S14: Based on the circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, and circuit breaker load data, design the state matrix of the circuit breaker spatial hierarchy data to generate the circuit breaker state matrix data.

[0090] As an embodiment of the present invention, reference Figure 2 As shown, Figure 1 A detailed flowchart of step S1 is shown below. In this embodiment, step S1 includes the following steps:

[0091] Step S11: The circuit breaker is monitored and processed by the sensor to obtain circuit breaker monitoring data, wherein the circuit breaker monitoring data includes circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, circuit breaker load data and circuit breaker connection data.

[0092] In this embodiment of the invention, a multi-type sensor combination device is deployed to monitor the circuit breaker in all aspects. For example, a microwave radio frequency sensor with a center frequency of 2.4 GHz and a bandwidth of 100 MHz is used to continuously collect radio frequency reflection signals from key parts such as circuit breaker contacts and terminals at a sampling interval of 100 milliseconds, accurately obtaining signal strength and phase information; a Hall current sensor with an accuracy of 0.2S and a voltage transformer are used to complete the acquisition of electrical parameters such as current, voltage, and power factor 10 times per second; an infrared thermal imager with a resolution of 640×480 pixels and a temperature measurement accuracy of ±2℃ is used to scan the surface of the circuit breaker at a rate of 5 frames per second to construct a temperature distribution map; a pressure sensor with a range of 0-1000N and a displacement sensor with a measurement accuracy of 0.01mm are combined to monitor the changes in contact pressure and mechanical displacement in real time; and a fiber optic sensor with a wavelength of 1310nm is used to accurately determine the closed and open states of the circuit breaker contacts through optical signal transmission. All data collected by the sensors are transmitted to the data acquisition terminal via the 485 bus, forming raw circuit breaker monitoring data that includes radio frequency, electrical, thermal, load, and connectivity information.

[0093] Step S12: Obtain circuit breaker design structure data, and perform unit topology analysis on circuit breaker connection data based on circuit breaker design structure data to generate circuit breaker unit topology data; perform time synchronization processing on circuit breaker unit topology data to generate time-synchronized circuit breaker unit topology data.

[0094] In this embodiment of the invention, circuit breaker design structure data is obtained by reading digital design drawings containing information such as 3D models, component parameters, and connection relationships. Using graph theory analysis, the contact connection relationships in the circuit breaker connection data are abstracted into a topological structure of nodes and edges. Each contact unit is assigned a unique identifier, constructing the circuit breaker unit topology structure. For example, the main contacts, auxiliary contacts, trip units, and other functional units of the circuit breaker are considered as nodes, and the electrical connections between contacts are considered as edges. A topology diagram that intuitively reflects the connection relationships of each unit is generated, and the physical coordinates and electrical parameters of each connection point are recorded, forming the circuit breaker unit topology structure data. To ensure data time consistency, a hardware clock synchronization method is used to timestamp each topology structure data to the microsecond level. By comparing the timestamps of each data, a linear interpolation algorithm is used to time-calibrate the topology structure data collected at different times, unifying all data under the same time reference, generating time-synchronized circuit breaker unit topology structure data, so that changes in the topology structure accurately match the actual operating state of the circuit breaker.

[0095] Step S13: Perform spatial hierarchy design of the circuit breaker based on the time-synchronous circuit breaker unit topology data, and generate circuit breaker spatial hierarchy data;

[0096] In this embodiment of the invention, the circuit breaker's spatial hierarchy is divided into component layer, functional module layer, and system layer according to its physical structure and function. At the component layer, based on the physical coordinates of the contacts in the topology data, the circuit breaker's contacts, springs, insulation components, and other components are modeled in three dimensions according to their actual spatial positions. At the functional module layer, components with the same function are grouped together; for example, arc-extinguishing components and operating mechanism components are categorized separately, clarifying the spatial boundaries and connection methods between modules. At the system layer, all functional modules are integrated to construct a complete circuit breaker spatial architecture. The spatial layout is optimized by calculating the spatial distances and interference between components and modules. For example, if the distance between the contact and a nearby insulation component is found to be less than a safety threshold (set to 5mm) when the contact operates, the contact trajectory or the insulation component position is adjusted. Finally, circuit breaker spatial hierarchy data containing component spatial coordinates, module hierarchical relationships, and the overall system architecture is formed, providing spatial dimension information for subsequent state analysis.

[0097] Step S14: Based on the circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, and circuit breaker load data, design the state matrix of the circuit breaker spatial hierarchy data to generate the circuit breaker state matrix data.

[0098] In this embodiment of the invention, a circuit breaker state matrix is ​​constructed based on the circuit breaker's radio frequency, electrical, thermal, load data, and spatial hierarchy data. A multi-dimensional matrix framework is established, using components in the spatial hierarchy data as matrix rows and time series data as matrix columns. Signal strength data collected by microwave radio frequency sensors is filled into the corresponding matrix rows according to the location of the corresponding components; current and voltage data collected by Hall current sensors and voltage transformers are normalized and mapped to the 0-1 interval, then filled into the corresponding time series columns; temperature data acquired by infrared thermal imagers is filled into the matrix as temperature values ​​based on the component temperature distribution characteristics. For circuit breaker load data, contact pressure data collected by pressure sensors and mechanical displacement data acquired by displacement sensors are filtered and converted into dimensionless values ​​before being filled into the matrix. For example, contact pressure is standardized by the ratio to rated pressure, and mechanical displacement is standardized by the ratio to maximum stroke.

[0099] Furthermore, step S2 includes the following steps:

[0100] Step S21: Based on the circuit breaker load data, perform load link analysis on the circuit breaker to generate load link data;

[0101] Step S22: Detect the status of the circuit breaker's interactive nodes based on the circuit breaker connection data, and generate interactive node status data;

[0102] Step S23: Based on the interactive node status data, perform circuit breaker on / off loop reconstruction processing on the load link data to generate on / off loop reconstruction data;

[0103] Step S24: Analyze the on / off changes of the circuit breaker based on the on / off circuit reconstruction data, and generate on / off change data;

[0104] Step S25: Based on the on / off change data, perform a transmission link stability assessment on the on / off circuit reconstruction data of the circuit breaker to generate transmission link stability assessment data;

[0105] Step S26: Based on the transmission link stability assessment data, perform electrical parameter correction processing on the circuit breaker state matrix data to generate corrected circuit breaker state matrix data.

[0106] As an embodiment of the present invention, reference Figure 3 As shown, Figure 1 A detailed flowchart of step S2 is shown below. In this embodiment, step S2 includes the following steps:

[0107] Step S21: Based on the circuit breaker load data, perform load link analysis on the circuit breaker to generate load link data;

[0108] In this embodiment of the invention, load link analysis is performed using circuit breaker load data. A pressure sensor and a displacement sensor are used in conjunction to collect circuit breaker load data. For example, the pressure sensor has a range of 0-1500N and an accuracy of 0.1N, collecting contact pressure every 100 milliseconds; the displacement sensor has a resolution of 0.01mm and simultaneously records the mechanical displacement of the contacts. The collected load data is transmitted to a data processing unit, and a mechanical model is established based on the connection relationships and mechanical transmission paths of the components in the circuit breaker's design structure. Taking a molded case circuit breaker as an example, the stress on the current transmission path is analyzed from changes in contact pressure. For example, if the contact pressure drops by 200N at a certain moment, the displacement sensor data is used to determine whether abnormal contact displacement has occurred. By analyzing the propagation path of the pressure change, the load-bearing capacity of components such as conductors and busbars connected to the contact is determined. These components are then marked sequentially according to the current transmission order to generate load link data. The load link data is presented in the form of a linked list, with each node containing information such as component name, stress parameters, and connection relationships.

[0109] Step S22: Detect the status of the circuit breaker's interactive nodes based on the circuit breaker connection data, and generate interactive node status data;

[0110] In this embodiment of the invention, the status of interactive nodes is detected using circuit breaker connectivity data. For example, the connectivity status of circuit breaker contacts is monitored in real time using an optical fiber sensor. The optical fiber sensor emits a light signal with a wavelength of 1310nm. When a contact is closed, the light signal is transmitted to the receiving end through the optical fiber, and the receiving end detects the change in light intensity; when a contact is open, the light signal is interrupted. The on / off status of each contact is recorded at 1-millisecond intervals. The contacts and terminals of the circuit breaker are considered as interactive nodes, and a node status detection table is established. For example, for a circuit breaker containing main contacts, auxiliary contacts, and multiple terminals, the detection table includes information such as "Node 1 (Main Contact 1) - Closed (Light Intensity Value 1000μW)" and "Node 2 (Auxiliary Contact 1) - Open (Light Intensity Value 0μW)". A threshold judgment is performed on the light intensity data of each node, setting a light intensity below 100μW as an open state and above 900μW as a closed state. If the light intensity exceeds the threshold range, it is marked as an abnormal state. Finally, interactive node status data containing the real-time on / off status of each interactive node and abnormal identification is generated.

[0111] Step S23: Based on the interactive node status data, perform circuit breaker on / off loop reconstruction processing on the load link data to generate on / off loop reconstruction data;

[0112] In this embodiment of the invention, the linked list structure in the load link data is traversed based on the on / off information of each node in the interactive node status data. For example, if a contact (such as main contact 1 in the interactive node status data) is detected to be in an open state, the connection path related to that contact in the load link data is cut off, and the current transmission path is replanned. For example, when main contact 1 is open, the current that originally passed through main contact 1 needs to be switched to a backup contact or bypass path. The node (such as auxiliary contact 2) adjacent to main contact 1 and in a closed state is found in the load link data, and the load link is reconnected as "wire X - auxiliary contact 2 - other components" to form a new on / off loop. The reconstructed on / off loop information is recorded in the form of a graph structure, where each node represents a component, the edges represent connection relationships, and the attributes of the edges include parameters such as current transmission direction and load capacity. On / off loop reconstruction data is generated to intuitively display the current effective current transmission path of the circuit breaker.

[0113] Step S24: Analyze the on / off changes of the circuit breaker based on the on / off circuit reconstruction data, and generate on / off change data;

[0114] In this embodiment of the invention, the on / off circuit reconstruction data at the current moment is compared with the data at the previous moment, and the on / off status is determined by the changes in the nodes and edges of the graph structure. For example, if a node or edge is added to the on / off circuit reconstruction data, it indicates that a new component or connection path has been added; if a node or edge disappears, it indicates that the corresponding component or connection has been disconnected. For example, comparing the on / off circuit diagrams at two different moments, it is found that the originally connected "auxiliary contact 2-bus Y" edge has disappeared, and a new "standby contact Z-bus Y" edge has been added, which indicates that the circuit breaker has switched on / off, and the current path has switched from auxiliary contact 2 to standby contact Z. The specific time of the on / off change, the components involved, the paths before and after the change, and other information are recorded to generate on / off change data, such as "path before change at a certain time: conductor X-auxiliary contact 2-bus Y, path after change: conductor X-standby contact Z-bus Y", which provides a basis for subsequent stability assessment.

[0115] Step S25: Based on the on / off change data, perform a transmission link stability assessment on the on / off circuit reconstruction data of the circuit breaker to generate transmission link stability assessment data;

[0116] In this embodiment of the invention, the load changes of each component in the on / off circuit reconstruction data are analyzed based on the path switching information recorded in the on / off change data. The fluctuation range of parameters such as current, voltage, and power of each component before and after the path switching is calculated. For example, when the current path switches from auxiliary contact 2 to standby contact Z, the current data of standby contact Z and its connected wires before and after the switching are obtained. If the current before the switching is 50A, and the current rises to 80A instantaneously after the switching, and the fluctuation range exceeds a certain range of the rated current, then the stability of the transmission chain is determined to be at risk. Stability assessment indicators, such as current fluctuation coefficient and voltage deviation rate, are set to quantitatively score the stability of each component. The score results of each component are compared with preset thresholds to generate transmission chain stability assessment data. The data includes information such as component name, stability score, and risk level (e.g., low risk, medium risk, high risk), comprehensively assessing the operational stability of the circuit breaker transmission chain.

[0117] Step S26: Based on the transmission link stability assessment data, perform electrical parameter correction processing on the circuit breaker state matrix data to generate corrected circuit breaker state matrix data.

[0118] In this embodiment of the invention, electrical parameters of the circuit breaker state matrix data are corrected based on transmission chain stability assessment data. The circuit breaker state matrix data is organized by component (rows) and time (columns), recording data such as radio frequency, electrical, and thermal properties of each component. Based on the risk level of each component in the transmission chain stability assessment data, the electrical parameters of the corresponding components in the state matrix are corrected. For components with low stability scores and high risk levels, such as a conductor deemed high-risk in the transmission chain stability assessment due to excessive current fluctuations potentially causing resistance changes, a resistance correction value is calculated based on the current fluctuation amplitude and the temperature coefficient of the conductor material (e.g., 0.0039 / ℃ for copper conductors). If current fluctuations cause an increase in conductor temperature, the resistance increases, and the resistance parameter corresponding to that conductor in the state matrix is ​​corrected. For all components with stability risks, their electrical parameters are corrected one by one in the above manner, ultimately generating corrected circuit breaker state matrix data to ensure that the state matrix accurately reflects the current actual operating state of the circuit breaker.

[0119] Furthermore, step S3 includes the following steps:

[0120] Step S31: Extract the radio frequency characteristics of the circuit breaker based on the circuit breaker radio frequency data to generate radio frequency characteristic data;

[0121] In this embodiment of the invention, radio frequency (RF) characteristics are extracted from the RF data of the circuit breaker. A microwave RF sensor with a center frequency of 2.4 GHz and a bandwidth of 200 MHz is used to continuously collect RF reflection signals from the circuit breaker contacts, conductive connections, and the surface of the insulating medium at 50 ms sampling intervals. These signals contain information such as component material, surface condition, and connection tightness. The collected raw RF data is first filtered by hardware to remove 50 Hz power frequency interference and other frequency band clutter, and then the time-domain signal is converted into a frequency-domain signal using Discrete Fourier Transform (DFT) to obtain the power spectral density distribution at 1 MHz intervals within the 0-2.4 GHz frequency band. For example, in a certain data collection, analysis revealed an abnormal peak in the power spectral density within the 2.35 GHz-2.38 GHz frequency band, with the peak intensity being 3 dB higher than that of adjacent frequency bands. Extract parameters such as center frequency, bandwidth, peak power, and phase offset of each frequency band to generate RF characteristic data containing multiple sets of frequency band features, such as "frequency band 2.35GHz-2.38GHz, center frequency 2.365GHz, bandwidth 3MHz, peak power -20dBm, phase offset 15°", etc.

[0122] Step S32: Perform electrical-composite frequency band analysis on the circuit breaker based on radio frequency characteristic data and circuit breaker electrical parameter data to generate electrical-composite frequency band data;

[0123] In this embodiment of the invention, electrical-composite frequency band analysis is performed based on radio frequency characteristic data and circuit breaker electrical parameter data. The circuit breaker electrical parameter data is acquired by a high-precision Hall current sensor (sampling frequency 100Hz) and a voltage transformer, containing information such as current, voltage, and power factor. First, based on the power spectral density distribution in the radio frequency characteristic data, the impact of radio frequency signals in each frequency band on current transmission is calculated. For example, when the radio frequency signal strength in the 2.35GHz-2.38GHz band exceeds -25dBm, it will cause a 5% fluctuation in current transmission in that band. This impact is superimposed and analyzed with the actual current data collected by the current transformer to identify the frequency bands with significant current fluctuations due to radio frequency interference. Simultaneously, a Fast Fourier Transform (FFT) is performed on the current signal in the electrical parameter data to extract the resonant frequency of the current. For example, analysis at a certain moment reveals that the current has resonant peaks at frequencies such as 500Hz and 1.2kHz. These current resonant frequencies are cross-referenced with the frequency bands in the RF characteristic data. When the current resonant frequency overlaps with or is close to the RF frequency band, an electrical-RF coupling resonance phenomenon is identified. For example, if the 500Hz current resonant frequency overlaps with the 490Hz-510Hz RF frequency band, the coupling strength, phase relationship, and other parameters of this frequency band are recorded to generate electrical-RF coupling resonance data. Finally, all coupling resonance frequency bands and related characteristic parameters are integrated, combined with the transmission characteristics of current and voltage in each frequency band, to form electrical-composite frequency band data that includes frequency range, coupling characteristics, and trends in electrical parameter changes.

[0124] Step S33: Perform thermal-electric spectrum correlation mapping processing on the circuit breaker based on the circuit breaker thermal energy data and electrical-composite frequency band data to generate thermal-electric spectrum correlation data;

[0125] In this embodiment of the invention, an infrared thermal imager with a resolution of 640×480 pixels and a temperature measurement accuracy of ±1℃ is used to collect surface temperature distribution data of the circuit breaker at a rate of 2 frames per second, forming a thermal image sequence containing the temperature value of each pixel. Time-domain analysis is performed on the thermal image sequence to calculate the rate of temperature change over time for each monitored area (such as contacts or terminals), generating thermal energy fluctuation data. For example, if the temperature in the contact area rises from 50℃ to 55℃ in 10 seconds, the rate of temperature change is 0.5℃ / s. The thermal energy fluctuation data is correlated with electrical-composite frequency band data to analyze the impact of temperature changes on voltage transmission characteristics. When electrical-radio frequency coupling resonance exists in a certain frequency band (e.g., 1.2kHz-1.5kHz) and the temperature in the corresponding area increases, the fluctuation of the voltage signal in that frequency band is observed. Assuming that for every 1℃ increase in temperature, the voltage amplitude in that frequency band increases by 2%, a temperature-voltage change relationship model is established through linear fitting. Spectral analysis is performed on the voltage signal to extract the voltage response frequency. The correspondence between each voltage response frequency and temperature change and frequency band characteristics is recorded to generate thermo-electric spectrum correlation data.

[0126] Step S34: Based on the thermal-electric spectrum correlation data, perform frequency band impedance change analysis on the corrected circuit breaker state matrix data to generate circuit breaker frequency band impedance data.

[0127] In this embodiment of the invention, the thermo-electric spectrum correlation data contains the coupling relationship and changing trend of the thermal and electrical characteristics of the circuit breaker in different frequency bands, while the modified circuit breaker state matrix data records multi-dimensional information such as radio frequency, electrical, and thermal energy of each component at different times. First, based on the thermo-electric spectrum correlation data, the abnormal disconnection attribute status of the circuit breaker in each frequency band is analyzed. For example, when thermo-electric coupling in a certain frequency band (2.3GHz-2.4GHz) causes voltage fluctuations exceeding 15% of the rated value and the temperature continues to rise, it is determined that there is an abnormal disconnection risk in that frequency band, and abnormal disconnection attribute status data is generated. Based on the abnormal disconnection attribute status data, a time-series on / off matrix is ​​constructed. Using time as the row and frequency band as the column, the on / off status and risk level of each frequency band at different times are marked in the matrix. For example, at the 10th second, the 2.3GHz-2.4GHz frequency band is marked as "disconnected, high risk". The time-series on / off matrix is ​​combined with the modified circuit breaker state matrix data, and for each frequency band, the impedance value is calculated using the voltage and current data at the corresponding time according to Ohm's law. Due to the influence of thermo-electric spectrum correlation on impedance, a temperature correction factor is introduced.

[0128] Furthermore, step S32 includes the following steps:

[0129] Step S321: Based on the radio frequency characteristic data and the circuit breaker electrical parameter data, perform current transmission fluctuation analysis of the circuit breaker to generate current transmission fluctuation data;

[0130] In this embodiment of the invention, current transmission fluctuation analysis is performed using radio frequency (RF) characteristic data and circuit breaker electrical parameter data. RF characteristic data is acquired by a microwave RF sensor with a center frequency of 2.4 GHz and a bandwidth of 200 MHz. This sensor records the RF reflected signal intensity and phase information of the circuit breaker contacts and conductive connections every 50 milliseconds. Circuit breaker electrical parameter data is acquired by a Hall current sensor with an accuracy of 0.2 and a voltage transformer. The current sensor samples at a frequency of 100 Hz to monitor current changes in real time. The RF characteristic data is processed to calculate the power spectral density for each frequency band. For example, in the 2.35 GHz-2.38 GHz band, the time-domain signal is converted to a frequency-domain signal using a fast Fourier transform, and the calculated power spectral density for this band is -20 dBm. Simultaneously, the current signal in the electrical parameter data is analyzed to extract the fundamental component and harmonic components of the current. The influence of the RF signal on current transmission is analyzed, and a mapping relationship between the RF frequency band and current harmonics is established. Subsequently, through cross-analysis of multiple frequency bands and current harmonics, the deviation in current transmission influence is calculated. For example, under the influence of radio frequency signals in the 2.35GHz-2.38GHz band, the deviation of the 5th harmonic current is 1A (5A × 20%). The resonant frequency of the current is extracted, and spectral analysis of the current signal reveals resonant peaks at frequencies such as 500Hz and 1.2kHz. The current transmission rate at each resonant frequency is calculated.

[0131] Step S322: Perform electrical-radio frequency coupling resonance mapping of the circuit breaker based on the current transmission fluctuation data to generate electrical-radio frequency coupling resonance data;

[0132] In this embodiment of the invention, the resonant frequency in the current transmission fluctuation data is compared and analyzed with the frequency band in the radio frequency characteristic data. For example, the current transmission fluctuation data shows a resonant peak at 500Hz, while the radio frequency characteristic data indicates a strong radio frequency signal in the 490Hz-510Hz frequency band. When the current resonant frequency overlaps with or is close to the radio frequency band, an electrical-radio frequency coupling resonance phenomenon is determined. For each coupling resonance point, the coupling strength and phase relationship are calculated. The coupling strength is determined by analyzing the ratio of the current fluctuation amplitude to the radio frequency signal strength. For example, in the 490Hz-510Hz frequency band, the radio frequency signal strength is -15dBm, corresponding to a current fluctuation amplitude of 10A at 500Hz, and the calculated coupling strength is -10dB. Simultaneously, the phase difference between the current signal and the radio frequency signal is analyzed to determine their phase relationship. A correspondence between the coupling resonance frequency and the circuit breaker components is established. By analyzing the position information of the radio frequency sensor and the current sensor, the physical component corresponding to each coupling resonance point is determined.

[0133] Step S323: Perform electrical-composite frequency band analysis on the circuit breaker based on the electrical-RF coupling resonance data to generate electrical-composite frequency band data.

[0134] In this embodiment of the invention, all frequency bands in the coupled resonance data are classified and integrated, and frequency bands with similar characteristics are grouped together. For example, frequency bands with coupling strength greater than -15dB are classified as strongly coupled frequency bands, frequency bands with coupling strength between -15dB and -25dB are classified as moderately coupled frequency bands, and frequency bands with coupling strength less than -25dB are classified as weakly coupled frequency bands. The electrical parameter variation characteristics of each frequency band group are analyzed. For strongly coupled frequency bands, the transmission characteristics of voltage and current in that frequency band are measured. For example, in the 490Hz-510Hz strongly coupled frequency band, the measured voltage amplitude attenuation is 5%, and the current phase shift is 20°. At the same time, the impedance characteristics within the frequency band are analyzed, and the equivalent impedance of the frequency band is obtained by calculating the voltage-to-current ratio. When coupled resonance exists between adjacent frequency bands, the energy transfer and interference between them are analyzed. The analysis results of all frequency bands are integrated. The first dimension is the frequency band range, the second dimension is the electrical parameters (voltage amplitude, current phase, impedance, etc.), and the third dimension is the characteristic parameters (coupling strength, energy transfer rate, etc.).

[0135] Furthermore, step S321 includes the following steps:

[0136] RF frequency strength is calculated based on RF characteristic data to generate RF frequency strength data.

[0137] In this embodiment of the invention, radio frequency intensity is calculated by processing radio frequency characteristic data. A microwave radio frequency sensor with a center frequency of 2.4 GHz and a bandwidth of 200 MHz is used to monitor the circuit breaker. This sensor continuously collects radio frequency reflected signals from the circuit breaker contacts, conductive connections, and the surface of the insulating medium with a sampling period of 50 milliseconds. The collected raw radio frequency signals are first preprocessed using a hardware filter to filter out 50 Hz power frequency interference and noise signals from other frequency bands, ensuring the purity of the input data. Then, the time-domain radio frequency signal is converted into a frequency-domain signal using Discrete Fourier Transform (DFT), dividing the 0-2.4 GHz frequency band into 200 sub-bands with 1 MHz intervals. For each sub-band, its power spectral density is calculated, specifically by averaging the squares of the signal amplitude within that band and taking the logarithm to obtain the power value in dBm.

[0138] Preferably, the current transmission influence deviation of the circuit breaker is evaluated based on the radio frequency intensity data, and current transmission influence deviation data is generated.

[0139] In this embodiment of the invention, a correspondence model between radio frequency intensity and current transmission interference is established. This model is constructed based on a large amount of historical experimental data, using the formula ΔI(f)=k·I norm(f) I0 calculates the deviation caused by current transmission at frequency f, where k is the coupling coefficient, I0 is the reference current value, and I norm This is the normalized current value at frequency f. The total influence deviation is obtained by summing the current transmission influence deviations at all frequency points. n represents the number of current transmission influence deviations across all frequency points. Simultaneously, the proportion of the current transmission influence deviation at each frequency point to the total deviation is calculated using the following formula: To assess the stability of the deviation, the standard deviation of the deviation due to the influence of current transmission is calculated. in The average deviation is calculated. The current transmission effect at each frequency point influences the deviation ΔI(f). i ), deviation percentage P ΔI (f i and total influence deviation ΔI total Standard deviation σ ΔI A comprehensive evaluation was conducted. The impact of changes in radio frequency intensity across different frequency bands on current transmission was clarified. For example, a 5 dBm increase in radio frequency intensity within the 2.3 GHz-2.4 GHz band leads to a 3% fluctuation in current transmission within the same band. Substituting the intensity values ​​for each frequency band from the radio frequency intensity data into the model, the corresponding impact on current transmission was calculated. For instance, if the radio frequency intensity in the 2.35 GHz-2.36 GHz band is -22 dBm, and this intensity changes to -17 dBm, the model calculates a 1.5% fluctuation in current transmission within this band. The calculated impact on current transmission was compared with the standard current transmission value to obtain the deviation value.

[0140] Preferably, the current resonant frequency is extracted based on the circuit breaker's electrical parameter data to generate current resonant frequency data;

[0141] In this embodiment of the invention, the current resonant frequency is extracted from the circuit breaker's electrical parameter data. A Hall current sensor with an accuracy of 0.2 is used to collect the circuit breaker's current signal in real time at a sampling frequency of 100Hz. This current signal contains the fundamental frequency and its harmonic components. A Fast Fourier Transform (FFT) is performed on the collected time-domain current signal to convert it to the frequency domain, obtaining the amplitude distribution of the current signal at different frequencies. For example, an amplitude threshold of 10% of the fundamental frequency amplitude is set. When the current amplitude at a certain frequency exceeds this threshold, this frequency is determined to be the current resonant frequency.

[0142] Preferably, the current transmission amount of the circuit breaker is calculated based on the current resonant frequency data to generate current transmission amount data;

[0143] In this embodiment of the invention, for each extracted current resonant frequency, the current transmission amount is calculated using Ohm's law based on its amplitude in the frequency domain and the impedance characteristics of the circuit. The impedance of the circuit at that frequency is calculated. For cases involving multiple resonant frequencies, the current transmission amounts corresponding to each resonant frequency are vector-synthesized. For example, the circuit breaker current signal has two resonant frequencies: 500Hz and 1200Hz. The current transmission amount at 500Hz is 8A with a phase of 0°, and the current transmission amount at 1200Hz is 5A with a phase of 30°. The synthesized total current transmission amount is calculated using trigonometric functions.

[0144] Preferably, the circuit breaker's current transmission fluctuation is analyzed based on the deviation data of current transmission influence to generate current transmission fluctuation data.

[0145] In this embodiment of the invention, current transmission fluctuation analysis is performed by combining current transmission influence deviation data and current transmission quantity data. The deviation value for each frequency band in the current transmission influence deviation data is superimposed onto the current transmission quantity for the same frequency band in the current transmission quantity data. For example, in the 2.35GHz-2.36GHz frequency band, the current transmission influence deviation data shows a deviation of 1.5A, while the current transmission quantity for this frequency band in the current transmission quantity data is 15A. Therefore, the current transmission quantity considering radio frequency influence becomes 16.5A. The fluctuation amplitude of the current transmission quantity for each frequency band is calculated using the formula... Among them I after I represents the current transfer amount after considering radio frequency effects. before Let F represent the original current transfer rate and F represent the fluctuation range of the current transfer rate. The above calculations are performed on all frequency bands to generate current transfer fluctuation data, which includes the frequency band range, the original current transfer rate, the current transfer rate considering radio frequency effects, and the current transfer fluctuation range. Simultaneously, the trends and patterns of current transfer fluctuations in each frequency band are analyzed.

[0146] Furthermore, step S33 includes the following steps:

[0147] Step S331: Perform thermal energy fluctuation analysis on the circuit breaker based on the circuit breaker thermal energy data, and generate thermal energy fluctuation data;

[0148] In this embodiment of the invention, thermal energy fluctuation analysis is performed on the thermal energy data of the circuit breaker. An infrared thermal imager with a resolution of 640×480 pixels and a temperature measurement accuracy of ±1℃ is used to continuously collect surface temperature data of the circuit breaker at a frequency of 2 frames per second. The thermal imager divides the circuit breaker surface into multiple temperature measurement areas, such as key parts like contacts, terminals, and arc-extinguishing chambers. Each area contains multiple pixels, and each pixel corresponds to a temperature value. For the acquired thermal image sequence, for each temperature measurement area, the temperature difference between corresponding pixels in two adjacent frames is calculated. For example, if the temperature of a pixel in the contact area is 50℃ in the first frame and changes to 52℃ in the second frame, the temperature difference is 2℃. The temperature difference of all pixels in each area is averaged to obtain the temperature change of that area. Simultaneously, the mean and variance of the temperature change per unit time (per second) are calculated. The mean reflects the average trend of temperature change, and the variance reflects the severity of temperature fluctuations.

[0149] Step S332: Based on thermal energy fluctuation data, perform voltage fluctuation analysis on electrical-composite frequency band data of the circuit breaker to generate voltage fluctuation data;

[0150] In this embodiment of the invention, voltage fluctuation analysis is performed on electrical-composite frequency band data based on thermal energy fluctuation data. The electrical-composite frequency band data includes characteristic parameters of the circuit breaker such as voltage, current, and radio frequency coupling at different frequency bands. Based on the temperature changes in each temperature measurement area in the thermal energy fluctuation data, its impact on the voltage transmission of the corresponding frequency band is analyzed. A temperature-voltage influence model is established, and the voltage data corresponding to each frequency band is extracted from the electrical-composite frequency band data, denoted as U(f,t), where f is the frequency and t is the time. For each time window, the voltage changes of each frequency band within that window are analyzed. For frequency band f... i Calculate the rate of change of voltage. Where Δt represents the time interval. For example, when the temperature in the contact area increases by 10°C, the voltage amplitude will decrease by 5% and the phase shift will increase by 10° in the 2.3GHz-2.4GHz frequency band. Substituting the temperature change from the thermal energy fluctuation data into this model, the changes in voltage amplitude and phase in each frequency band are calculated.

[0151] Step S333: Analyze the voltage response frequency of the circuit breaker based on the voltage fluctuation data to generate voltage response frequency data;

[0152] In this embodiment of the invention, for each frequency band in the voltage fluctuation data, a Fast Fourier Transform (FFT) is performed on the voltage amplitude and phase changes over time to convert the time-domain signal into a frequency-domain signal, obtaining the amplitude distribution of the voltage signal at different frequencies. An amplitude threshold is set; when the voltage signal amplitude at a certain frequency exceeds 8% of the fundamental amplitude, that frequency is determined to be the voltage response frequency. For example, after performing FFT analysis on the voltage fluctuation data in the 2.3GHz-2.4GHz frequency band, it is found that, in addition to the fundamental frequency, the voltage amplitude at 2.35GHz and 2.38GHz reaches 10% and 12% of the fundamental amplitude, respectively. Therefore, 2.35GHz and 2.38GHz are determined to be the voltage response frequencies for that frequency band.

[0153] Step S334: Perform thermo-electric spectrum correlation mapping processing based on voltage response frequency data and electrical-composite frequency band data to generate thermo-electric spectrum correlation data.

[0154] In this embodiment of the invention, thermo-electric spectrum correlation mapping is performed on voltage response frequency data and electrical-composite frequency band data. A three-dimensional mapping coordinate system is established, with frequency band as the X-axis, frequency as the Y-axis, and temperature as the Z-axis. Each frequency point in the voltage response frequency data is marked on the XY plane according to its frequency band and frequency value, and its position on the Z-axis is determined according to the corresponding temperature change. The thermo-electric correlation degree of that frequency band is calculated. Where ΔU T (f) represents the voltage fluctuation in this frequency band after considering the thermal effect, U eff (f) represents the effective voltage value for this frequency band. σ represents the average temperature change within the time window. TThis represents the standard deviation of temperature change within a time window. For example, in the 2.3GHz-2.4GHz frequency band, if the contact area temperature corresponding to the 2.35GHz voltage response frequency increases by 20℃, this point is marked at (2.3GHz-2.4GHz, 2.35GHz, 20℃) in the coordinate system. Combining the voltage, current, and RF coupling characteristics of this frequency band from the electrical-composite frequency band data, each marked point is assigned corresponding attribute information, such as voltage amplitude change rate, current transmission efficiency, and RF coupling strength. The correlation between different marked points is analyzed. If multiple points show a clustering trend in the XY plane and have similar temperature changes in the Z-axis direction, it indicates that these frequency points are affected by temperature in similar ways. The correlation characteristics between heat, electricity, and the spectrum are visually displayed in the coordinate system using lines and color coding.

[0155] Furthermore, step S34 includes the following steps:

[0156] Step S341: Analyze the abnormal tripping control attribute status of the circuit breaker based on the thermal-electric spectrum correlation data, and generate abnormal tripping control attribute status data;

[0157] In this embodiment of the invention, abnormal disconnection attribute status analysis of circuit breakers is performed using thermoelectric spectrum correlation data. The thermoelectric spectrum correlation data is presented in a three-dimensional mapped coordinate system, where the X-axis represents the frequency band, the Y-axis represents the frequency, and the Z-axis represents the temperature. Each data point includes attribute information such as voltage amplitude change rate, current transmission efficiency, and radio frequency coupling strength. Hardware filters are used to preprocess the thermoelectric spectrum correlation data, filtering out 50Hz power frequency interference and noise signals from other frequency bands to ensure the purity of the input data. For example, an abnormal threshold is set; when the voltage amplitude change rate of a certain frequency band exceeds 15%, the current transmission efficiency is less than 80%, or the radio frequency coupling strength is higher than -15dBm, it is determined that there is an abnormal disconnection risk in that frequency band. For example, in the 2.35GHz-2.38GHz frequency band, the voltage amplitude change rate is 18%, the current transmission efficiency is 75%, and the radio frequency coupling strength is -12dBm, all exceeding the abnormal threshold, indicating a high-risk abnormal disconnection in that frequency band. The above analysis was performed on all frequency bands, with abnormal frequency bands marked in red and normal frequency bands marked in green, forming a visual distribution map of abnormal frequency band outages. Simultaneously, the spatial distribution characteristics of abnormal frequency bands were analyzed; if multiple adjacent frequency bands simultaneously exhibited abnormalities, a regional risk of abnormal frequency band outages was identified.

[0158] Step S342: Perform timing on / off matrix analysis of the circuit breaker based on the abnormal disconnection attribute status data, and generate timing on / off matrix data;

[0159] In this embodiment of the invention, each abnormal frequency band in the abnormal disconnection control attribute status data is arranged in chronological order to establish a time-series on / off matrix. Rows in the matrix represent time, columns represent frequency bands, and element values ​​are 0 or 1; 0 indicates the frequency band is in an off state at that moment, and 1 indicates the frequency band is in a conducting state at that moment. For each abnormal frequency band, its on / off state changes at different times are analyzed. For example, in the 2.35GHz-2.38GHz frequency band, it is in a conducting state at the 10th second (element value 1), in an off state at the 15th second (element value 0), and in a conducting state again at the 20th second (element value 1). The on / off frequency of each frequency band is calculated, that is, the number of times the on / off state changes per unit time. For example, if the on / off state of the 2.35GHz-2.38GHz frequency band changes 5 times in 1 minute, then the on / off frequency of this frequency band is 5 times / minute. Analyzing the on / off correlation between adjacent frequency bands, if the on / off state changes of two adjacent frequency bands have similar temporal patterns, then it is determined that these two frequency bands have an on / off correlation. For example, the on / off state changes of the 2.35GHz-2.38GHz band and the 2.38GHz-2.41GHz band are completely consistent at the 10th, 15th, and 20th seconds, indicating that these two frequency bands have a strong on / off correlation.

[0160] Step S343: Based on the timing on / off matrix data, perform frequency band impedance change analysis on the corrected circuit breaker state matrix data to generate circuit breaker frequency band impedance data.

[0161] In this embodiment of the invention, frequency band impedance variation analysis of circuit breaker electrical parameters is performed based on time-series on / off matrix data and modified circuit breaker state matrix data. The modified circuit breaker state matrix data records radio frequency, electrical, and thermal data of each component at different times. The time-series on / off matrix data includes the on / off state, on / off frequency, and on / off correlation information for each frequency band at different times. For each frequency band, voltage and current data at the corresponding time are extracted from the modified circuit breaker state matrix data based on the on / off state in the time-series on / off matrix data. The trend of frequency band impedance variation over time is analyzed. If the impedance value of a certain frequency band changes drastically in a short period of time, it is determined that there is an impedance anomaly in that frequency band, and the original impedance value Z of each frequency band is extracted from the modified circuit breaker state matrix data. original(f) Extract the on / off states M(t,f) of each frequency band at different time points from the time-series on / off matrix data. For each frequency band f, calculate its impedance correction coefficient α(t,f) under different on / off states, using the formula α(t,f)=1+β×(1―M(t,f)), where β is the impedance change coefficient. For example, in the 2.35GHz-2.38GHz frequency band, the impedance value is 44Ω at the 10th second and changes to 60Ω at the 15th second, a change of 36%, indicating an impedance anomaly in this frequency band. Combine the on / off frequencies and on / off correlation information in the time-series on / off matrix data to analyze the relationship between impedance anomalies and changes in on / off states. For example, it is found that the impedance anomaly in the 2.35GHz-2.38GHz frequency band is closely related to the high-frequency on / off state changes in this band. Integrate the impedance values, impedance change trends, and impedance anomaly information of all frequency bands to generate circuit breaker frequency band impedance data. At the same time, an impedance anomaly early warning mechanism is established. When the impedance change rate of a certain frequency band exceeds 20%, an early warning signal is triggered, providing key data support for the operation status assessment and fault diagnosis of circuit breakers.

[0162] Furthermore, step S4 includes the following steps:

[0163] Step S41: Perform frequency band division processing on the circuit breaker frequency band impedance data to generate circuit breaker frequency band impedance data.

[0164] In this embodiment of the invention, a hardware filter is used to preprocess the circuit breaker frequency band impedance data to filter out 50Hz power frequency interference and noise signals from other frequency bands, ensuring the purity of the input data. For example, an impedance change rate threshold of 10% is set. When the impedance change rate of a certain frequency band exceeds this threshold, the frequency band is determined to be a sensitive frequency band; when the impedance change rate is less than 5%, the frequency band is determined to be a stable frequency band; and when the impedance change rate is between 5% and 10%, the frequency band is determined to be a transitional frequency band. For example, in the 2.35GHz-2.38GHz frequency band, the impedance change rate is 18%, and the frequency band is determined to be a sensitive frequency band; in the 2.45GHz-2.48GHz frequency band, the impedance change rate is 3%, and the frequency band is determined to be a stable frequency band; in the 2.40GHz-2.43GHz frequency band, the impedance change rate is 7%, and the frequency band is determined to be a transitional frequency band. The above analysis is performed on all frequency bands, and sensitive frequency bands are marked in red, stable frequency bands in green, and transitional frequency bands in yellow, forming a visual distribution map of the affected frequency bands. Simultaneously, the spatial distribution characteristics of sensitive frequency bands are analyzed. If multiple adjacent frequency bands are simultaneously sensitive, a sensitive frequency band clustering region is identified. For example, if five consecutive 1MHz sub-bands within the 2.3GHz-2.4GHz frequency band are all sensitive, this region is identified as a sensitive frequency band clustering region.

[0165] Step S42: Analyze the frequency band impedance response characteristics based on the circuit breaker frequency band impedance data to generate frequency band impedance response characteristic data.

[0166] In this embodiment of the invention, the impedance value of each frequency band is analyzed over time. A differential amplifier is used to perform differential processing on the impedance data, and the rate of change and acceleration of change of impedance are calculated. For example, in the sensitive frequency band of 2.35GHz-2.38GHz, the rate of change of impedance obtained through differential processing is 1.2Ω / s, and the acceleration of change is 0.1Ω / s. 2 The periodic characteristics of impedance changes were analyzed, and Fourier transform was used to convert the time-domain impedance change data into frequency-domain data to identify the main frequency components of the impedance changes. For example, in the 2.35GHz-2.38GHz frequency band, the Fourier transform results showed that the main frequency components of impedance changes were 50Hz and 100Hz. The correlation between the frequency band impedance response and external factors, such as temperature, humidity, and voltage, was analyzed. A multiple regression model was established, with impedance value as the dependent variable and temperature, humidity, and voltage as independent variables, and the regression coefficients were solved using the least squares method.

[0167] Step S43: Calculate the frequency band impedance fluctuation of the circuit breaker based on the frequency band impedance response characteristic data, and generate frequency band impedance fluctuation data;

[0168] In this embodiment of the invention, the impedance fluctuation amplitude is calculated for each frequency band. The root mean square (RMS) method is used to calculate the RMS value of the impedance fluctuation by squaring, averaging, and taking the square root of the rate of change of impedance. For example, in the 2.35GHz-2.38GHz frequency band, the RMS value of the impedance change rate is 0.8Ω / s. The frequency characteristics of the impedance fluctuation are analyzed using a spectrum analyzer to identify the main frequency components and their energy distribution. For example, in the 2.35GHz-2.38GHz frequency band, the spectrum analysis results show that the main frequency components of the impedance fluctuation are 50Hz and 100Hz, with the 50Hz frequency component accounting for 60% of the total energy. The correlation between impedance fluctuation and frequency band sensitivity is analyzed. If the impedance fluctuation amplitude in sensitive frequency bands is significantly greater than that in stable frequency bands, a difference in fluctuation sensitivity is determined. For example, in the sensitive frequency band of 2.35GHz-2.38GHz, the RMS value of impedance fluctuation is 0.8Ω / s; in the stable frequency band of 2.45GHz-2.48GHz, the RMS value of impedance fluctuation is 0.2Ω / s. The impedance fluctuation amplitude in the sensitive frequency band is 4 times that in the stable frequency band, indicating a significant difference in fluctuation sensitivity.

[0169] Step S44: Analyze the circuit breaker's tripping delay deviation based on the frequency band impedance fluctuation data, and generate tripping delay deviation data;

[0170] In this embodiment of the invention, the impact of impedance fluctuations on the circuit breaker's tripping response time is analyzed for each frequency band. An impedance fluctuation-tripping response time model is established, based on a large amount of historical experimental data, clarifying the influence of impedance fluctuations on tripping response time in different frequency bands. For example, when the RMS value of impedance fluctuations in the 2.3GHz-2.4GHz frequency band increases by 0.1Ω / s, the circuit breaker's tripping response time increases by 0.5ms. Substituting the RMS value of impedance fluctuations for each frequency band into the model, the corresponding increase in tripping response time is calculated. For example, in the 2.35GHz-2.38GHz frequency band, the RMS value of impedance fluctuations is 0.8Ω / s, and the model calculates an increase of 4ms in the tripping response time for this frequency band. The calculated increase in tripping response time is compared with the standard tripping response time to obtain the deviation value. Calculations are performed sequentially for all frequency bands to generate control delay deviation data, which includes the frequency band range, impedance fluctuation RMS value, increase in control response time, and control delay deviation value. This quantifies the impact of impedance fluctuations in different frequency bands on the circuit breaker's control response time. Simultaneously, the spatial distribution characteristics of the control delay deviation are analyzed. If the control delay deviation values ​​of multiple adjacent frequency bands are similar, a region of control delay deviation clustering is identified.

[0171] Step S45: Analyze the control of the circuit breaker's linkage nodes based on the control delay deviation data, and generate linkage node control data;

[0172] In this embodiment of the invention, the impact of the control delay deviation on the circuit breaker linkage nodes is analyzed for each frequency band. A control delay deviation-linkage node impact model is established. This model is constructed based on the physical structure and electrical connection relationships of the circuit breaker, clarifying the degree of impact of the control delay deviation on each linkage node in different frequency bands. For example, in the 2.3GHz-2.4GHz frequency band, every 1ms increase in the control delay deviation leads to a 0.3ms delay in the action time of the contact node and a 0.5℃ increase in the temperature of the terminal block node. The control delay deviation value for each frequency band in the control delay deviation data is substituted into the above model to calculate the corresponding linkage node impact parameters. For example, in the 2.35GHz-2.38GHz frequency band, the control delay deviation is 4ms. According to the model calculation, the action time delay of the contact node in this frequency band is 1.2ms, and the temperature increase of the terminal block node is 2℃. Calculations are performed sequentially for all frequency bands to generate linkage node impact data containing the frequency band range, control delay deviation value, and linkage node impact parameters. The interaction relationships between each linkage node are analyzed, and a linkage node network model is established. This model uses nodes to represent the various components of a circuit breaker, edges to represent the physical connections and electrical coupling relationships between components, and edge weights to indicate the strength of the influence between nodes. For example, there is a strong connection between the contact node and the terminal node, with an influence strength of 0.8; and a weak connection between the contact node and the arc-extinguishing chamber node, with an influence strength of 0.3. Based on the linkage node network model, the propagation path and influence range of the control delay deviation in the network are analyzed. For example, when the control delay deviation in the 2.35GHz-2.38GHz frequency band affects the contact node, the linkage node network model analysis shows that the influence will propagate through the path of contact node-terminal node-busbar node, ultimately affecting the stability of the entire circuit.

[0173] Step S46: Calculate the electrical node parameters of the circuit breaker based on the linkage node control data, and generate electrical node parameter data;

[0174] In this embodiment of the invention, the changes in the electrical parameters of each linkage node are analyzed. Voltage and current sensors are used to monitor the voltage and current values ​​of each node in real time, and a temperature sensor is used to monitor the temperature of each node. For example, for the contact node, the voltage measured by the voltage sensor is 220V, the current measured by the current sensor is 5A, and the temperature measured by the temperature sensor is 60℃. Based on the influencing parameters in the linkage node control data, the changes in the electrical parameters of each node are calculated. For example, under the influence of the control delay deviation in the 2.35GHz-2.38GHz frequency band, the action time delay of the contact node is 1.2ms. Based on the physical characteristics and electrical connection relationship of the contact node, it is calculated that the voltage will decrease by 5V, the current will increase by 0.2A, and the temperature will increase by 2℃. The calculated changes are superimposed with the original electrical parameter values ​​to obtain the corrected electrical parameter values. For example, the corrected voltage value of the contact node is 215V, the current value is 5.2A, and the temperature value is 62℃. Calculations are performed sequentially on all linkage nodes to generate electrical node parameter data, including node name, original electrical parameter value, change, and corrected electrical parameter value. Simultaneously, the interrelationships between the electrical parameters of each node are analyzed to establish an electrical parameter correlation model. For example, through statistical analysis of a large amount of historical data, a correlation model between contact node voltage and current values ​​is established.

[0175] Step S47: Based on the electrical node parameter data and the linkage node control data, perform parameter coordination configuration of the circuit breaker to generate circuit breaker parameter coordination configuration data.

[0176] In this embodiment of the invention, for each linkage node, its optimal operating parameter range is calculated based on the corrected electrical parameter values ​​and influencing parameters. A multi-objective optimization algorithm is used, with node stability, energy consumption, and lifespan as optimization objectives, and node physical characteristics and electrical connection relationships as constraints, to solve for the optimal operating parameters. For example, for the contact node, the multi-objective optimization algorithm calculates that, under the current operating conditions, its optimal voltage range is 210V-220V, its optimal current range is 4.8A-5.2A, and its optimal temperature range is 55℃-65℃. The parameter coordination relationships between each linkage node are analyzed, and a parameter coordination network model is established. This model uses nodes to represent the various components of the circuit breaker, edges to represent the parameter coordination relationships between components, and the weight of the edges to represent the coordination strength between nodes. For example, there is a strong coordination relationship between the contact node and the terminal node, with a coordination strength of 0.9; there is a weak coordination relationship between the contact node and the arc-extinguishing chamber node, with a coordination strength of 0.4. Based on the parameter coordination network model, the propagation path and influence range of parameter configuration in the network are analyzed. For example, when adjusting the voltage value of a contact node, analysis using a parameter coordination network model shows that the adjustment will propagate through the path from the contact node to the terminal block node to the busbar node, ultimately affecting the stability of the entire circuit. A parameter coordination algorithm is used to calculate the optimal adjustment amount for each node's parameters, ensuring that the parameters of each node meet the requirements of the optimal operating parameter range while being coordinated.

[0177] Furthermore, step S5 includes the following steps:

[0178] Step S51: Obtain real-time power demand data, calculate the demand impact range of the real-time power demand data, and generate demand impact range data;

[0179] In this embodiment of the invention, real-time power demand data is acquired, and its impact range is calculated. Real-time power demand data is collected by smart meters installed at various nodes of the power system. These smart meters have a measurement accuracy of 0.2 and collect data such as voltage, current, and power every 100 milliseconds. The collected data is transmitted to a data processing center via power line carrier communication, forming a real-time power demand dataset containing parameters such as timestamps, node locations, voltage values, current values, active power, and reactive power. The real-time power demand data is preprocessed, using a low-pass filter to remove high-frequency noise and ensure data accuracy. The entire power grid is divided into several regions, each containing several power nodes. For each region, the impact range is calculated. Based on the active power of each node within the region, a weighted distance method is used to calculate the impact range. For example, setting the distance weighting coefficient α = 0.8 and the power weighting coefficient β = 0.2, for any node i and node j within the region, the impact value of node i on node j is calculated using the formula: Where d ijP represents the physical distance between node i and node j (obtained through a power grid geographic information system, in kilometers). i Let P be the active power of node i. total This represents the sum of active power of all nodes within the region. Then, the radius R of the demand impact range for each region is calculated using the formula: Where n is the number of nodes in the region.

[0180] Step S52: Based on the demand impact range data, sort the real-time power demand data to generate sorted real-time power demand data;

[0181] In this embodiment of the invention, firstly, demand priority assessment indicators are defined, including demand urgency, scope of impact, and severity of impact. Demand urgency is determined based on the load type and importance of the nodes; for example, the demand urgency for important loads such as hospitals and government agencies is high, while the demand urgency for ordinary residential loads is low. Scope of impact is determined based on the number and distribution area of ​​affected nodes; the more affected nodes and the wider the distribution area, the larger the scope of impact. Severity of impact is determined based on the voltage change rate and current change rate; the greater the change rate, the more severe the impact. Then, a demand priority assessment model is constructed. Demand impact scope data and real-time power demand data are input into the model, and a comprehensive priority score for each node's demand is calculated. For example, node A has a high demand urgency (weight 0.4), a medium scope of impact (weight 0.3), and a high severity of impact (weight 0.3), resulting in a comprehensive priority score of 85 points calculated by the model. Finally, the demands of all nodes are sorted from high to low according to their comprehensive priority scores, generating sorted real-time power demand data. For example, the sorting results show that node A has the highest priority, followed by node C, node B, node D, and so on.

[0182] Step S53: Based on the sorted real-time power demand data, perform coordinated circuit breaker parameter configuration on the circuit breaker to generate coordinated circuit breaker control data, and perform on / off operations on the circuit breaker through the coordinated circuit breaker control data.

[0183] In this embodiment of the invention, firstly, a circuit breaker collaborative disconnection configuration model is established. This model is constructed based on the power system topology and circuit breaker distribution, clarifying the electrical connection relationships and collaborative control logic between each circuit breaker. For example, when node A has the highest demand priority and needs to increase power supply, the model calculates that circuit breakers B1, B2, and B3 need to be closed simultaneously to ensure smooth power transmission from the power source node to node A. Then, the sorted real-time power demand data and circuit breaker parameter coordination configuration data are input into the collaborative disconnection configuration model to calculate the optimal on / off state and action time for each circuit breaker. For example, for circuit breaker B1, the calculated optimal on / off state is closed, with an action time of 50 milliseconds after receiving the control signal; for circuit breaker B2, the optimal on / off state is closed, with an action time of 70 milliseconds; and for circuit breaker B3, the optimal on / off state is closed, with an action time of 100 milliseconds. Next, collaborative disconnection data is generated, which includes parameters such as the identifier of each circuit breaker, optimal on / off state, action time, and action sequence. For example, the coordinated disconnection control data shows that circuit breaker B1 (ID001) is closed, with an operating time of 50 milliseconds and an operating sequence of 1; circuit breaker B2 (ID002) is closed, with an operating time of 70 milliseconds and an operating sequence of 2; and circuit breaker B3 (ID003) is closed, with an operating time of 100 milliseconds and an operating sequence of 3. Finally, the coordinated disconnection control data is converted into electrical signals by the control circuit and transmitted to the actuators of each circuit breaker, controlling the circuit breakers to perform on / off operations according to the specified on / off states and operating times.

[0184] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0185] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A control method for a solid-state intelligent circuit breaker, characterized in that, Includes the following steps: Step S1: Monitor the circuit breaker using sensors to obtain circuit breaker monitoring data, which includes circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, circuit breaker load data, and circuit breaker connection data; design the circuit breaker state matrix based on the circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, and circuit breaker load data to generate circuit breaker state matrix data; Step S1 includes the following steps: Step S11: The circuit breaker is monitored and processed by the sensor to obtain circuit breaker monitoring data, wherein the circuit breaker monitoring data includes circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data, circuit breaker load data and circuit breaker connection data. Step S12: Obtain circuit breaker design structure data, and perform unit topology analysis on circuit breaker connection data based on circuit breaker design structure data to generate circuit breaker unit topology data; perform time synchronization processing on circuit breaker unit topology data to generate time-synchronized circuit breaker unit topology data. Step S13: Perform spatial hierarchy design of the circuit breaker based on the time-synchronous circuit breaker unit topology data, and generate circuit breaker spatial hierarchy data; Step S14: Based on the circuit breaker radio frequency data, circuit breaker electrical parameter data, circuit breaker thermal energy data and circuit breaker load data, design the state matrix of the circuit breaker spatial hierarchy data to generate the circuit breaker state matrix data. Step S2: Analyze the on / off changes of the circuit breaker based on the circuit breaker load data and circuit breaker connection data to generate on / off change data; perform electrical parameter correction processing on the circuit breaker state matrix data based on the on / off change data to generate corrected circuit breaker state matrix data. Step S3: Based on the circuit breaker radio frequency data, circuit breaker electrical parameter data, and circuit breaker thermal energy data, calculate the frequency band impedance change of the circuit breaker electrical parameters on the modified circuit breaker state matrix data to generate circuit breaker frequency band impedance data. Step S4: Based on the circuit breaker frequency band impedance data, perform parameter coordination configuration of the circuit breaker to generate circuit breaker parameter coordination configuration data; Step S5: Obtain real-time power demand data; perform coordinated circuit breaker control analysis on the corrected circuit breaker state matrix data based on the real-time power demand data and circuit breaker parameter coordination configuration data to generate coordinated circuit breaker control data; perform on / off operations on the circuit breaker based on the coordinated circuit breaker control data.

2. The solid-state intelligent circuit breaker control method according to claim 1, characterized in that, Step S2 includes the following steps: Step S21: Based on the circuit breaker load data, perform load link analysis on the circuit breaker to generate load link data; Step S22: Detect the status of the circuit breaker's interactive nodes based on the circuit breaker connection data, and generate interactive node status data; Step S23: Based on the interactive node status data, perform circuit breaker on / off loop reconstruction processing on the load link data to generate on / off loop reconstruction data; Step S24: Analyze the on / off changes of the circuit breaker based on the on / off circuit reconstruction data, and generate on / off change data; Step S25: Based on the on / off change data, perform a transmission link stability assessment on the on / off circuit reconstruction data of the circuit breaker to generate transmission link stability assessment data; Step S26: Based on the transmission link stability assessment data, perform electrical parameter correction processing on the circuit breaker state matrix data to generate corrected circuit breaker state matrix data.

3. The solid-state intelligent circuit breaker control method according to claim 1, characterized in that, Step S3 includes the following steps: Step S31: Extract the radio frequency characteristics of the circuit breaker based on the circuit breaker radio frequency data to generate radio frequency characteristic data; Step S32: Perform electrical-composite frequency band analysis on the circuit breaker based on radio frequency characteristic data and circuit breaker electrical parameter data to generate electrical-composite frequency band data; Step S33: Perform thermal-electric spectrum correlation mapping processing on the circuit breaker based on the circuit breaker thermal energy data and electrical-composite frequency band data to generate thermal-electric spectrum correlation data; Step S34: Based on the thermal-electric spectrum correlation data, perform frequency band impedance change analysis on the corrected circuit breaker state matrix data to generate circuit breaker frequency band impedance data.

4. The solid-state intelligent circuit breaker control method according to claim 3, characterized in that, Step S32 includes the following steps: Step S321: Based on the radio frequency characteristic data and the circuit breaker electrical parameter data, perform current transmission fluctuation analysis of the circuit breaker to generate current transmission fluctuation data; Step S322: Perform electrical-radio frequency coupling resonance mapping of the circuit breaker based on the current transmission fluctuation data to generate electrical-radio frequency coupling resonance data; Step S323: Perform electrical-composite frequency band analysis on the circuit breaker based on the electrical-RF coupling resonance data to generate electrical-composite frequency band data.

5. The solid-state intelligent circuit breaker control method according to claim 4, characterized in that, Step S321 includes the following steps: RF frequency strength is calculated based on RF characteristic data to generate RF frequency strength data. Based on radio frequency intensity data, the deviation of current transmission impact of circuit breakers is evaluated, and current transmission impact deviation data is generated. The current resonant frequency is extracted based on the circuit breaker's electrical parameter data to generate current resonant frequency data. The current transmission amount of the circuit breaker is calculated based on the current resonant frequency data, and the current transmission amount data is generated. Based on the deviation data of current transmission influence, the current transmission fluctuation of the circuit breaker is analyzed using the current transmission quantity data, and current transmission fluctuation data is generated.

6. The solid-state intelligent circuit breaker control method according to claim 3, characterized in that, Step S33 includes the following steps: Step S331: Perform thermal energy fluctuation analysis on the circuit breaker based on the circuit breaker thermal energy data, and generate thermal energy fluctuation data; Step S332: Based on thermal energy fluctuation data, perform voltage fluctuation analysis on electrical-composite frequency band data of the circuit breaker to generate voltage fluctuation data; Step S333: Analyze the voltage response frequency of the circuit breaker based on the voltage fluctuation data to generate voltage response frequency data; Step S334: Perform thermo-electric spectrum correlation mapping processing based on voltage response frequency data and electrical-composite frequency band data to generate thermo-electric spectrum correlation data.

7. The solid-state intelligent circuit breaker control method according to claim 3, characterized in that, Step S34 includes the following steps: Step S341: Analyze the abnormal tripping control attribute status of the circuit breaker based on the thermal-electric spectrum correlation data, and generate abnormal tripping control attribute status data; Step S342: Perform timing on / off matrix analysis of the circuit breaker based on the abnormal disconnection attribute status data, and generate timing on / off matrix data; Step S343: Based on the timing on / off matrix data, perform frequency band impedance change analysis on the corrected circuit breaker state matrix data to generate circuit breaker frequency band impedance data.

8. The solid-state intelligent circuit breaker control method according to claim 1, characterized in that, Step S4 includes the following steps: Step S41: Perform frequency band division processing on the circuit breaker frequency band impedance data to generate circuit breaker frequency band impedance data. Step S42: Analyze the frequency band impedance response characteristics based on the circuit breaker frequency band impedance data to generate frequency band impedance response characteristic data. Step S43: Calculate the frequency band impedance fluctuation of the circuit breaker based on the frequency band impedance response characteristic data, and generate frequency band impedance fluctuation data; Step S44: Analyze the circuit breaker's tripping delay deviation based on the frequency band impedance fluctuation data, and generate tripping delay deviation data; Step S45: Analyze the control of the circuit breaker's linkage nodes based on the control delay deviation data, and generate linkage node control data; Step S46: Calculate the electrical node parameters of the circuit breaker based on the linkage node control data, and generate electrical node parameter data; Step S47: Based on the electrical node parameter data and the linkage node control data, perform parameter coordination configuration of the circuit breaker to generate circuit breaker parameter coordination configuration data.

9. The solid-state intelligent circuit breaker control method according to claim 1, characterized in that, Step S5 includes the following steps: Step S51: Obtain real-time power demand data, calculate the demand impact range of the real-time power demand data, and generate demand impact range data; Step S52: Based on the demand impact range data, sort the real-time power demand data to generate sorted real-time power demand data; Step S53: Based on the sorted real-time power demand data, perform coordinated circuit breaker parameter configuration on the circuit breaker to generate coordinated circuit breaker control data, and perform on / off operations on the circuit breaker through the coordinated circuit breaker control data.

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