A defect positioning method and device of a high-voltage cable, an electronic device, and a medium

Abstract

This invention belongs to the field of power equipment fault diagnosis technology, and discloses a method, device, electronic equipment, and medium for locating defects in high-voltage cables. The method includes acquiring discharge signals corresponding to multiple sensors; calculating the coarse time difference and fine time difference in the frequency domain for different discharge signals arriving at their respective sensors; weighting and fusing the coarse time difference and fine time difference to obtain a target time difference; and determining the location of the discharge defect based on the target time difference, signal propagation speed, and the coordinates of each sensor. This invention solves the problem of inaccurate location in existing technologies.

Description

Technical Field

[0001] This invention relates to the field of power equipment fault diagnosis technology, and in particular to a method, device, electronic equipment and medium for locating defects in high-voltage cables. Background Technology

[0002] As a key power transmission equipment in the power system, the operating status of high-voltage cables and their accessories directly affects the stability and safety of the power system. Nowadays, there are many ways to deal with discharge defects, which can accurately identify the discharge type of accessories to achieve efficient cable maintenance. In order to solve the discharge problem of accessories more efficiently, it is also necessary to accurately locate the discharge defects.

[0003] Traditional discharge diagnosis and localization mainly rely on a single sensor and human experience. This method of judgment, with its reliance on a single data source and manual judgment, is prone to large localization errors.

[0004] Therefore, those skilled in the art are dedicated to developing an intelligent diagnostic technology that can automatically and accurately locate the position of cable discharge defects, solving the problem of inaccurate positioning by traditional methods. Summary of the Invention

[0005] In view of the above-mentioned deficiencies of the prior art, the technical problem to be solved by the present invention is to provide a method, device, electronic device and medium for locating defects in high-voltage cables.

[0006] To achieve the above objectives, the present invention provides a method for locating defects in high-voltage cables. The method includes: acquiring discharge signals corresponding to multiple sensors; calculating the coarse time difference and fine time difference in the frequency domain for different discharge signals arriving at their respective sensors; weighting and fusing the coarse time difference and the fine time difference in the frequency domain to obtain a target time difference; and determining the location of the discharge defect based on the target time difference, the signal propagation speed, and the coordinates of each sensor.

[0007] To address the aforementioned technical problems, another technical solution adopted in this application is: a defect location device for high-voltage cables is provided. This device includes: an acquisition module configured to acquire discharge signals corresponding to multiple sensors; a calculation module configured to calculate the time-domain coarse time difference and frequency-domain fine time difference of different discharge signals arriving at their respective sensors, and to perform weighted fusion of the time-domain coarse time difference and the frequency-domain fine time difference to obtain a target time difference; and a location module configured to determine the location of the discharge defect based on the target time difference, the signal propagation speed, and the coordinates of each sensor.

[0008] To solve the above-mentioned technical problems, another technical solution adopted in this application is: to provide an electronic device, including a memory and a processor, wherein the memory stores program instructions, and the processor retrieves the program instructions from the memory to execute the above-mentioned target attribute identification method.

[0009] To solve the above-mentioned technical problems, another technical solution adopted in this application is to provide a computer-readable storage medium including program data, which is used to implement the above-mentioned target attribute identification method when executed by a processor.

[0010] The beneficial effects of this invention are as follows: This invention acquires discharge signals corresponding to multiple sensors; calculates the coarse time difference in the time domain and the fine time difference in the frequency domain for different discharge signals arriving at their respective sensors; weights and fuses the coarse time difference in the time domain and the fine time difference in the frequency domain to obtain the target time difference; and determines the location of the discharge defect based on the target time difference, the signal propagation speed, and the coordinates of each sensor. This achieves precise localization of partial discharge defects, improving diagnostic accuracy and positioning precision. Attached Figure Description

[0011] Figure 1 This is a schematic flowchart of a defect location method for high-voltage cables provided in an embodiment of this application;

[0012] Figure 2 This is a schematic diagram of a defect location device for a high-voltage cable provided in an embodiment of this application;

[0013] Figure 3 This is a schematic diagram of the electronic device provided in the embodiments of this application. Detailed Implementation

[0014] The present invention will be further described below with reference to the accompanying drawings and embodiments. It should be noted that in the description of the present invention, the terms "first", "second", "third", etc. are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0015] The location of discharge defects in high-voltage cable accessories (such as joints, terminations, intermediate joints, etc.) is affected by a single sensor and cannot effectively utilize the spatiotemporal correlation information of multi-source signals, resulting in a large error in the location of discharge points. Therefore, this application provides an intelligent diagnostic technology that can automatically and accurately locate the location of discharge defects in cable accessories.

[0016] Figure 1 This is a schematic flowchart of a defect location method for high-voltage cables provided in an embodiment of this application. The method includes:

[0017] S1, acquire discharge signals corresponding to multiple sensors.

[0018] Specifically, based on a pre-set sensor deployment, discharge signals from multiple sensors can be acquired. The sensor deployment balances signal acquisition efficiency and installation feasibility. Ultra-high frequency (UHF) sensors and ultrasonic sensors are used as components of the heterogeneous sensor array in this application. The sensors are deployed differently according to the structural characteristics of the 220kV cable accessories (such as the circumferential structure of the joint and the axial extension structure of the terminal head), simultaneously acquiring UHF and ultrasonic signals generated by partial discharge to obtain multi-source heterogeneous discharge signals, ensuring comprehensive and targeted signal acquisition. In this application, sensors can be pre-installed at each cable accessory for real-time collection of discharge signals to determine the location of discharge defects. Alternatively, sensors can be installed after the discharge at the cable accessory is known to be occurring, allowing for precise location of discharge defects; no limitation is imposed here.

[0019] As examples, for cable mid-joints, a "circumferentially evenly distributed + axially supplemented" pattern can be used. Three UHF sensor mounting points (spacing = joint circumference / 3) and three ultrasonic sensor mounting points (alternating with the UHF sensors) can be marked circumferentially on the joint body. Two ultrasonic sensor mounting points are marked 5cm axially at both ends of the joint. This allows for accurate discharge signals to be obtained based on the deployed sensors. For cable terminations, a "radial layering + top coverage" pattern can be used. Three layers of UHF sensor mounting points (two per layer, symmetrically distributed) are marked on the radial insulation jacket of the termination, and four ultrasonic sensor mounting points (evenly distributed) are marked on the top skirt area.

[0020] After the sensors are deployed, all sensors can be calibrated. This is done by using a pre-installed partial discharge simulator (output voltage 0-10kV, supporting simulation of three types of discharge) to calibrate each sensor individually: a simulated discharge signal is generated at a known location (reference point), the sensor's signal attenuation coefficient and delay time are recorded, and the data is stored in the system database. The calibration error is ≤5%. There are no restrictions here.

[0021] It should be understood that the signal characteristics of discharge signals from different sensors are not the same. For example, UHF sensors are used to acquire transient electromagnetic radiation generated at the moment of discharge, with a discharge signal frequency range of 300MHz-1GHz; ultrasonic sensors are used to acquire elastic waves / sound waves generated inside insulating materials during discharge, with a frequency range of 20kHz-2MHz. However, both share a commonality: they acquire instantaneously occurring spike signals, and their time-domain characteristics typically exhibit a pulse-like pattern of instantaneous rise and rapid decay. Further details will not be elaborated upon here.

[0022] To enable the defect location system to acquire the discharge signals collected by each sensor in real time, a data acquisition card with a built-in analog-to-digital converter can be used to connect the digital system and the sensors, thereby enabling the digital system (defect location system) to acquire the discharge signals. Of course, there are no restrictions here.

[0023] The term "sensor" as used in this application refers only to sensors installed on the same accessory.

[0024] This allows for the targeted deployment of sensors based on different cable accessories, and the calibration of each sensor. Different discharge signals can be obtained from different sensors, enabling the system to collect discharge signals from different sensors for defect location and judgment.

[0025] S2, calculate the coarse time difference in the time domain and the fine time difference in the frequency domain for different discharge signals to reach the corresponding sensor, and then perform weighted fusion of the coarse time difference in the time domain and the fine time difference in the frequency domain to obtain the target time difference.

[0026] Specifically, the target time difference can be calculated using a time difference calculation module. This module combines coarse matching in the time domain with fine calibration calculation of phase matching in the frequency domain to obtain the target time difference for discharge defect localization. When fusing the coarse time difference in the time domain and the fine time difference in the frequency domain, for example, the weight corresponding to the coarse time difference in the time domain is 0.7 and the weight corresponding to the fine time difference in the frequency domain is 0.3, the coarse time difference in the time domain and the fine time difference in the frequency domain are multiplied by their corresponding weights and added together to obtain the target time difference τ_final = 0.7 × τ1 + 0.3 × τ2. The fusion weights can be experimentally verified to combine the advantages of coarse matching in the time domain and fine correction in the frequency domain to improve the accuracy of the target time difference. Experiments have verified that the accuracy of the target time difference can reach within 3 ns (the smaller the time difference, the smaller the error).

[0027] S3. Determine the location of the discharge defect based on the target time difference, signal propagation speed, and coordinate information of each sensor.

[0028] Specifically, coordinate information can be obtained based on a pre-constructed three-dimensional coordinate system. By acquiring the coordinate information of each sensor within the same coordinate system, the positional relationship between different sensors can be obtained. Combined with the target time difference of the signal and the positional relationship of the sensors, the discharge location defect can be obtained.

[0029] Using the reference point of the cable accessory (such as the center of the joint or the bottom of the terminal head) as the origin of the preset three-dimensional coordinate system, the cable laying direction is verified as the x-axis, the vertical direction as the y-axis, and the horizontal direction perpendicular to the x-axis as the z-axis. There are no restrictions here, as long as it is reasonable. In this way, the three-dimensional coordinates of each sensor relative to the reference point of the cable accessory can be measured by a laser rangefinder to obtain laser ranging information. GPS positioning data is obtained through Global Positioning Information (GPS). The laser ranging and GPS positioning data are jointly calibrated, that is, the laser ranging information is corrected by GPS positioning data to obtain the coordinate information corresponding to each sensor.

[0030] Of course, the coordinate information of the sensors can also be dynamically calibrated periodically. As an example, during system operation, a "calibration cycle" is automatically started every 24 hours. Using the partial discharge simulation signal of the known location (a miniature discharge simulator built into the reference point of the cable accessory), the signal attenuation coefficient and delay time of each sensor are recalculated, the system database is updated, and the sensor drift caused by long-term operation is corrected to ensure the accuracy of the sensor position information and thus ensure the accuracy of discharge defect location.

[0031] According to the technical solution provided in the above embodiments, by acquiring discharge signals corresponding to multiple sensors and calculating the target time difference of discharge signals corresponding to different sensors, and then combining the signal propagation speed and the coordinate information of the sensors, the specific location of discharge defects in the cable accessories can be determined. By using multi-sensor positioning, the positioning error can be reduced, and the accurate location of discharge defects can be obtained.

[0032] In some embodiments, calculating the time-domain coarse time difference and frequency-domain fine time difference of different discharge signals arriving at the corresponding sensors includes: aligning the timestamps of each discharge signal received by different sensors to obtain aligned discharge signals; determining and saving the valid signals corresponding to each aligned discharge signal to obtain the valid pulse segment signals corresponding to each discharge signal; and calculating the time-domain coarse time difference and frequency-domain fine time difference based on each valid pulse segment signal.

[0033] Specifically, since there may be slight deviations in the time of data collection by various sensors (e.g., the internal clocks of the sensors are not synchronized), the discharge signals collected by all sensors can be aligned according to the timestamps through the GPS timing module to ensure that the time base of each discharge signal is consistent.

[0034] After alignment, the effective pulse segment signal corresponding to each discharge signal is determined. The effective pulse segment signal represents the pulse signal that truly represents the discharge event in the discharge signal. Determining the effective pulse segment signal can avoid the influence of noise on the judgment of the discharge defect location.

[0035] Coarse time difference in the time domain can be calculated by comparing the difference in the start or peak positions of the effective pulse segments on different sensors. For example, if sensor A captures a pulse at 0.001 seconds and sensor B captures a pulse at 0.0015 seconds, their coarse time difference is approximately 0.5 milliseconds. Fine time difference in the frequency domain, on the other hand, can be calculated by comparing the phase difference of the same frequency components on different sensors, thus deducing a more precise time difference. No restrictions are placed on this here.

[0036] According to the technical solution provided in the above embodiments, by aligning the discharge signals from different sensors with timestamps and determining the effective pulse segment signals of each discharge signal, and further calculating the coarse time difference in the time domain and the fine time difference in the frequency domain based on the effective pulse segment signals, the positioning range can be quickly located through timestamp alignment. It can also avoid the time difference error caused by the simple time domain or simple frequency domain methods in the calculation of dual time differences, thus laying the foundation for improving positioning accuracy.

[0037] In some embodiments, determining and saving the valid signals corresponding to each discharge signal after alignment to obtain the valid pulse segment signal corresponding to each discharge signal includes: segmenting each discharge signal after alignment according to the discharge pulse period to obtain the segmented pulse corresponding to each discharge signal; retaining the valid signals in the segmented pulse corresponding to each discharge signal whose pulse detection results meet the pulse result threshold to obtain the valid pulse segment signal; when the amplitude of the segmented pulse is greater than the amplitude threshold and the rise time is less than the rise time threshold, the pulse detection result meets the pulse result threshold.

[0038] Specifically, the aligned discharge signals can be segmented according to the discharge pulse period, with each segment lasting 2ms and containing one complete discharge pulse. A pulse detection algorithm is used to filter out valid pulse segments, i.e., to determine whether a valid discharge pulse is actually captured within each 2ms segment window, and invalid segments of the invalid discharge signals are discarded. The pulse detection algorithm can be used to determine whether the pulse detection result meets the pulse result threshold.

[0039] Furthermore, the amplitude threshold can be adaptively set according to environmental changes (such as inside a transformer or at the cable laying site). For example, 0.5pC is not limited here. If the peak value of the segmented pulse signal is lower than this threshold, it means that the sensor may not detect it at all, or it may just be background noise. If the peak value (maximum amplitude) of the segmented pulse is greater than or equal to this amplitude threshold, it is considered to be a valid pulse for discharge signal identification. However, to further ensure the validity of the pulse, it can be judged based on the rise time. If the rise time of the segmented pulse is less than the rise time threshold (e.g., 50ns), it means that its rise time is fast enough, which indicates that it may be a real discharge pulse.

[0040] In this embodiment of the application, when both the amplitude threshold and the rise time threshold are met, it can be preliminarily identified as a valid pulse segment signal. If the signal amplitude is too small (below the amplitude threshold) or the rise time is not fast enough (too long) within a certain 2ms window, this window will be regarded as an invalid segment and will be rejected.

[0041] According to the technical solution provided in the above embodiments, weak signals are filtered out by amplitude threshold and slow-changing signals that are not discharged are filtered out by rising edge time threshold, thereby extracting high-quality data, eliminating noise and invalid data, and ensuring that subsequent analysis (such as time difference calculation and energy estimation) is based only on real discharge signals.

[0042] In some embodiments, the coarse time difference in the time domain and the fine time difference in the frequency domain are calculated based on each effective pulse segment signal, including: calculating the coarse time difference in the time domain by performing weighted cross-correlation on each effective pulse segment signal, wherein the weight value of the weighted cross-correlation is positively correlated with the signal amplitude of the effective pulse segment signal.

[0043] Specifically, a weighted cross-correlation function can be used to assign dynamic weights to the effective pulse segment signal. The larger the amplitude of the effective pulse segment signal, the higher the weight. For example, the signal amplitude can be normalized to obtain the corresponding weight ratio of the weighted cross-correlation function; no restrictions are placed here. The weighted cross-correlation function can be: R_xy(τ)=Σ[w(x(t))×x(t)×y(t+τ)] / Σ[w(x(t))×w(y(t))], where w(x(t))=x(t) / max(x(t)), x(t) and y(t) are the signals from the two sensors, t is time, τ is the time difference, and R_xy(τ) is the weighted cross-correlation result, suppressing noise interference on the cross-correlation peak. In this way, the τ value corresponding to the peak of the weighted cross-correlation function can be found, which is used as the time-domain coarse time difference τ1, and the error range of this time-domain coarse time difference can be controlled within 5ns.

[0044] This allows for the calculation of the coarse time difference in the time domain using a weighted cross-correlation function, which lays the foundation for the subsequent target time difference.

[0045] In some embodiments, calculating the precise time difference in the frequency domain based on each effective pulse segment signal includes: performing a Fourier transform on the effective pulse segment to obtain the amplitude spectrum and phase spectrum corresponding to each discharge signal, and extracting the main frequency band of the signal from the amplitude spectrum; calculating the phase difference and the time difference of the main frequency band of each effective pulse segment signal, and calculating the time difference corresponding to each frequency point in the main frequency band based on the linear relationship between the phase difference and the time difference of the main frequency band of each effective pulse segment signal, wherein the phase difference is determined based on the phase information of the main frequency band; and performing a weighted average calculation on the time difference corresponding to each frequency point to obtain the precise time difference in the frequency domain, wherein the weight of the weighted average is determined based on the amplitude spectrum energy.

[0046] Specifically, a Fourier transform is performed on the effective pulse segment signal to obtain the amplitude spectrum and phase spectrum corresponding to each discharge signal. The phase information of the main frequency band is extracted from the amplitude spectrum, where the main frequency band can be 300MHz-1.5GHz for UHF and 40kHz-500kHz for ultrasound. The main frequency band is the region where the signal energy (amplitude) is most concentrated, and the signal-to-noise ratio is usually the highest and interference is the least in this frequency band. The phase information of the main frequency band can bridge the amplitude (frequency characteristics) and time difference (time characteristics). Based on the phase information, the phase difference of signals in different effective pulse segments can be obtained. For example, a Fourier transform is performed on the signals received by two sensors to obtain their frequency domain representations X1(f) and X2(f), respectively. The phase spectrum, i.e., φ1(f) and φ2(f), is extracted from X1(f) and X2(f). For each specific frequency point f in the main frequency band, their phase difference Δφ=φ2(f)-φ1(f) can be calculated, that is, the degree to which the signals of the two sensors are staggered on the time axis.

[0047] Based on the linear relationship between phase difference and time difference, the time difference corresponding to each frequency point within the main frequency band can be calculated. This linear relationship can be expressed as: Δφ = 2πfτ, where f is the frequency point and τ_f is the time difference corresponding to each frequency point. After calculating the time difference for each frequency point, a weighted average is calculated for each time difference, and this weighted average result is used as the frequency domain precise time difference τ2. It should also be noted that when calculating the weighted average for each time difference, the amplitude spectrum energy is used as the weight value, or the normalized amplitude spectrum energy is used as the weight value, and the normalized result is used as the corresponding weight value; no limit is imposed here.

[0048] According to the technical solution provided in the above embodiments, by processing the effective pulse segment signal, the weighted average value of the time difference corresponding to each frequency point of the effective pulse segment signal is calculated as the frequency domain fine time difference, which can ensure that accurate and reliable time difference information can still be obtained under heavy environment.

[0049] In some embodiments, determining the location of a discharge defect based on a target time difference, signal propagation speed, and the coordinates of each sensor includes: constructing a spherical equation corresponding to each sensor based on the signal propagation speed, sensor coordinates, target time difference, and preset discharge coordinates, with the sensor as the center and the distance from the sensor to the discharge location coordinates as the radius; calculating the minimum intersection region of each spherical equation to obtain a candidate region for determining the location of the discharge defect; iteratively selecting initial discharge coordinates from the candidate region based on an objective function, the objective function being constructed with the goal of minimizing the sum of squared errors between the measured propagation time and the theoretical propagation time of the sensor; and outputting the target discharge coordinates of the discharge defect location when the coordinate difference between two adjacent iterations of the objective function does not exceed a first target threshold, or the objective function value does not exceed a second target threshold.

[0050] Specifically, to construct the spherical equation and obtain the discharge coordinates, we can first preset the discharge coordinates P(x,y,z), let the coordinates of the i-th sensor be S_i(x_i,y_i,z_i), the signal propagation speed be v (for UHF signals, the speed of light is c=3×10^8m / s, and for ultrasonic signals, it is 340m / s), and the target time difference be τ_ij (the target time difference between sensor i and j; it should be noted that τ_final includes τ_ij). Then, based on the equality of radii, we construct the spherical equation: (x-x_i)^2+(y-y_i)^2+(z-z_i)^2=(v×t_i)^2, where t_i Let i be the signal propagation time from P to S_i. This propagation time can be calculated using the propagation time of the reference sensor and the target time difference. The reference sensor can be the sensor that acquires the discharge signal in the shortest time. The shortest time indicates the closest distance to the discharge location and the smallest error. Using the target time difference τ_ij between the reference sensor and other sensors, calculated previously, the signal propagation time t_i of the other sensors can be calculated. Then, by multiplying the signal propagation speed by the corresponding sensor's signal propagation time, the distance from the discharge location to the corresponding sensor, i.e., the radius, can be obtained: (v × t_i). Furthermore, the distance between the two points can be obtained by applying the Pythagorean theorem to the preset discharge coordinates and sensor coordinates.

[0051] √[(x-x_i)^2+(y-y_i)^2+(z-z_i)^2];

[0052] This allows us to construct the spherical equation for each sensor, then select suitable sensors, and solve for the intersection region of the selected sensors. This can be done by calculating the intersection of all spherical equations, or by selecting the three sensors that meet the requirements (e.g., the three farthest sensors, or at least three sensors that have an intersection). Here, the three farthest sensors are preferred to ensure that the spherical intersection region is minimized.

[0053] The initial discharge coordinates are then iteratively selected from the candidate region. This iterative process can be achieved by constructing an objective function, namely, a function that minimizes the sum of squared errors between the measured propagation time and the theoretical propagation time from the sensor, i.e., J(x,y,z)=Σ[(√[(x-x_i)^2+(y-y_i)^2+(z-z_i)^2] / v-t_i)^2]; where (√[(x-x_i)^2+(y-y_i)^2+(z-z_i)^2] / v is the theoretical propagation time, and t_i is the measured propagation time calculated using the target time difference. This allows for iterative selection of coordinates within the candidate region, minimizing the difference between the theoretical and measured propagation times to each sensor. The final target discharge coordinates are output when the distance difference between the iteratively selected coordinates on adjacent sides does not exceed the first target threshold (e.g., 0.01mm), or when the value of the iteratively obtained objective function does not exceed the second target threshold (e.g., 1e-6).

[0054] Of course, in the actual experiment, the target discharge coordinates are statically verified: a partial discharge simulator (discharge point location known, error ≤0.1mm) is used for testing, ensuring the positioning error is ≤0.3mm (1.2mm for the traditional least squares algorithm), and no limit is imposed here. Dynamic verification: on the 220kV cable accessories on site, the known defect location (marked by manual inspection) is located to meet the needs of maintenance personnel for accurate inspection.

[0055] In practical operation, environmental parameters (temperature, humidity, etc.) of the sensor can be collected in real time to establish an error correction model. Based on this error correction model, the calculation parameters for locating discharge defects can be corrected in real time, further improving the positioning accuracy in complex environments. As an example, for every 10°C change in temperature, the UHF signal propagation speed is corrected by 0.1%, and the ultrasonic signal propagation speed is corrected by 1%; for every 20% change in humidity, the ultrasonic signal propagation speed is corrected by 0.5%. No restrictions are imposed here.

[0056] According to the technical solution provided in the above embodiments, by constructing a spherical equation with the sensor as the center based on the radius, and by solving the intersection of the spherical equations, candidate regions are obtained. By constructing an objective function and iteratively selecting each coordinate in the candidate regions, the target discharge coordinates are obtained. In this way, by using the spatial geometric constraints (spherical equations) of multiple sensors to locate discharge defects, the accuracy of the location can be significantly improved. This solves the pain points of insufficient accuracy, poor anti-interference ability, and slow calculation speed of traditional discharge location, and greatly improves the accuracy, speed and robustness of discharge defect location, providing a strong technical guarantee for the preventive maintenance of power systems.

[0057] In some embodiments, the iteration rules for the objective function include: selecting the center point of the candidate region as the initial iteration point, and dynamically adjusting the iteration step size based on the objective criterion; the dynamic adjustment rules include: increasing the iteration step size according to the first rule when the objective function decreases after each iteration, and decreasing the iteration step size according to the second rule when the objective function increases.

[0058] First, a decrease in the objective function (J(x,y,z)) means that the error calculated using the newly found coordinates (the difference between the theoretical propagation time and the measured propagation time) has decreased. This indicates that we are moving in the correct direction (towards the optimal solution), and the iteration is effective. An increase in the objective function means that the error calculated using the newly found coordinates has increased. This suggests that we may have overshot our bounds (the step size is too large) or the direction is off, and the iteration is ineffective.

[0059] Therefore, selecting the center point of the candidate region as the initial iteration point can avoid the initial point being far from the optimal solution, thus increasing the workload. The iteration step size is adjusted by using an objective criterion (such as the Armijo criterion). The initial step size can be 0.1 mm. After each iteration, if the objective function value decreases, the step size is increased according to the first rule (e.g., if it decreases, the step size is multiplied by 1.2). If the objective function value increases, the step size is decreased according to the second rule (if it increases, the step size is multiplied by 0.5) to ensure iteration efficiency.

[0060] The objective function iteration can also introduce a momentum term, with the momentum coefficient set to 0.9. This utilizes the gradient information from the previous iteration to accelerate convergence and avoid getting trapped in local optima. No restrictions are imposed here.

[0061] According to the technical solution provided in the above embodiments, the entire process can be automated without human intervention, from signal acquisition, defect location, and alarm push, with a diagnostic delay of ≤500ms, which greatly improves diagnostic efficiency.

[0062] Figure 2 This is a schematic diagram of a defect location device for a high-voltage cable provided in an embodiment of this application, as shown below. Figure 2 As shown, the device includes:

[0063] The acquisition module 201 is configured to acquire discharge signals corresponding to multiple sensors;

[0064] The calculation module 202 is configured to calculate the coarse time difference in the time domain and the fine time difference in the frequency domain when different discharge signals arrive at the corresponding sensors, and to perform weighted fusion of the coarse time difference in the time domain and the fine time difference in the frequency domain to obtain the target time difference;

[0065] The positioning module 203 is configured to determine the location of the discharge defect based on the target time difference, signal propagation speed and the coordinates of each sensor.

[0066] In some embodiments, the calculation module 202 is specifically used to align the timestamps of the discharge signals received by different sensors to obtain the aligned discharge signals; determine and save the valid signals corresponding to the aligned discharge signals to obtain the valid pulse segment signals corresponding to each discharge signal; and calculate the coarse time difference in the time domain and the fine time difference in the frequency domain based on each valid pulse segment signal.

[0067] In some embodiments, the calculation module 202 is specifically used to segment each aligned discharge signal according to the discharge pulse period to obtain segmented pulses corresponding to each discharge signal; retain the valid signals in the segmented pulses corresponding to each discharge signal whose pulse detection results meet the pulse result threshold to obtain valid pulse segment signals; when the amplitude of the segmented pulse is greater than the amplitude threshold and the rise time is less than the rise time threshold, the pulse detection result meets the pulse result threshold.

[0068] In some embodiments, the calculation module 202 is specifically used to calculate the coarse time difference in the time domain by performing weighted cross-correlation on each effective pulse segment signal, and the weight value of the weighted cross-correlation is positively correlated with the amplitude of the effective pulse segment signal.

[0069] In some embodiments, the calculation module 202 is specifically used to perform Fourier transform on the effective pulse segment signal to obtain the amplitude spectrum and phase spectrum of each effective pulse segment signal; calculate the phase difference of the corresponding effective pulse segment signal based on different phase spectra; calculate the time difference corresponding to each frequency point in the main frequency band based on the linear relationship between the time difference of different effective pulse segment signals and the corresponding phase difference, and determine the phase difference based on the phase information of the main frequency band; and perform weighted average calculation on the time difference corresponding to each frequency point to obtain the frequency domain precise time difference, and determine the weight of the weighted average based on the amplitude spectrum energy.

[0070] In some embodiments, the positioning module 203 is specifically used to construct a spherical equation corresponding to each sensor based on the signal propagation speed, sensor coordinates, target time difference, and preset discharge coordinates. The spherical equation has the sensor as the center and the distance from the sensor to the discharge position coordinates as the radius. The minimum intersection region of each spherical equation is calculated to obtain a candidate region for determining the location of the discharge defect. Initial discharge coordinates are iteratively selected from the candidate region based on an objective function. The objective function is constructed with the goal of minimizing the sum of squared errors between the measured propagation time and the theoretical propagation time of the sensor. When the coordinate difference between two adjacent iterations of the objective function does not exceed a first target threshold, or the objective function value does not exceed a second target threshold, the target discharge coordinates of the discharge defect location are output.

[0071] In some embodiments, the positioning module 203 is specifically used to select the center point of the candidate region as the initial iteration point and dynamically adjust the iteration step size based on the target criterion; the dynamic adjustment rules include: if the objective function decreases after each iteration, the iteration step size is increased according to the first rule, and if the objective function increases, the iteration step size is decreased according to the second rule.

[0072] Figure 3 This is a schematic diagram of the electronic device 3 provided in an embodiment of this application. Figure 3 As shown, the electronic device 3 of this embodiment includes: a processor 301, a memory 302, and a computer program 303 stored in the memory 302 and executable on the processor 301. When the processor 301 executes the computer program 303, it implements the steps in the various method embodiments described above. Alternatively, when the processor 301 executes the computer program 303, it implements the functions of each module / unit in the various device embodiments described above.

[0073] Electronic device 3 can be a desktop computer, laptop, handheld computer, cloud server, or other electronic device. Electronic device 3 may include, but is not limited to, processor 301 and memory 302. Those skilled in the art will understand that... Figure 3 This is merely an example of electronic device 3 and does not constitute a limitation on electronic device 3. It may include more or fewer components than shown, or different components.

[0074] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0075] The memory 302 can be an internal storage unit of the electronic device 3, such as a hard disk or memory of the electronic device 3. The memory 302 can also be an external storage device of the electronic device 3, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 3. The memory 302 can also include both internal and external storage units of the electronic device 3. The memory 302 is used to store computer programs and other programs and data required by the electronic device.

[0076] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0077] If integrated modules / units are implemented as software functional units and sold or used as independent products, they can be stored in a storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program may include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. Computer-readable media may include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0078] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method for locating defects in high-voltage cables, characterized in that, include: S1, acquire discharge signals corresponding to multiple sensors; S2, calculate the coarse time difference in the time domain and the fine time difference in the frequency domain for different discharge signals arriving at the corresponding sensor, and perform weighted fusion of the coarse time difference in the time domain and the fine time difference in the frequency domain to obtain the target time difference; S3. Determine the location of the discharge defect based on the target time difference, signal propagation speed, and coordinates of each sensor.

2. The method according to claim 1, characterized in that, The calculation of the coarse time difference in the time domain and the fine time difference in the frequency domain for different discharge signals arriving at the corresponding sensors includes: The discharge signals received by different sensors are timestamped to obtain the aligned discharge signals. The effective signals corresponding to each of the aligned discharge signals are determined and saved to obtain the effective pulse segment signals corresponding to each of the discharge signals; Based on each of the effective pulse segment signals, the coarse time difference in the time domain and the fine time difference in the frequency domain are calculated.

3. The method according to claim 2, characterized in that, The process of determining and saving the effective signals corresponding to each of the aligned discharge signals to obtain the effective pulse segment signals corresponding to each discharge signal includes: The aligned discharge signals are segmented according to the discharge pulse period to obtain the segmented pulses corresponding to each discharge signal. The effective signals that satisfy the pulse result threshold in the segmented pulses corresponding to each discharge signal are retained to obtain the effective pulse segment signals; when the amplitude of the segmented pulse is greater than the amplitude threshold and the rise time is less than the rise time threshold, the pulse detection result satisfies the pulse result threshold.

4. The method according to claim 2, characterized in that, The calculation of the coarse time difference in the time domain based on each of the effective pulse segment signals includes: The time-domain coarse time difference is calculated by performing weighted cross-correlation on each of the effective pulse segment signals, and the weight value of the weighted cross-correlation is positively correlated with the amplitude of the effective pulse segment signal.

5. The method according to claim 2, characterized in that, The calculation of the frequency domain precise time difference based on each of the effective pulse segment signals includes: Perform a Fourier transform on the effective pulse segment signal to obtain the amplitude spectrum and phase spectrum of each effective pulse segment signal; calculate the phase difference of the corresponding effective pulse segment signal based on the different phase spectra; Based on the linear relationship between the time difference and the corresponding phase difference of different effective pulse segment signals, the time difference corresponding to each frequency point in the main frequency band is calculated, and the phase difference is determined based on the phase information of the main frequency band. The frequency domain precise time difference is obtained by performing a weighted average calculation on the time difference corresponding to each frequency point. The weights of the weighted average are determined based on the amplitude spectrum energy.

6. The method according to claim 1, characterized in that, The step of determining the location of the discharge defect based on the target time difference, signal propagation speed, and coordinates of each sensor includes: Based on the signal propagation speed, the sensor coordinates, the target time difference, and the preset discharge coordinates, a spherical equation corresponding to each sensor is constructed, with the sensor as the center and the distance from the sensor to the discharge position coordinates as the radius. The minimum intersection region of each of the spherical equations is calculated to obtain a candidate region for determining the location of the discharge defect; Initial discharge coordinates are iteratively selected from the candidate regions based on an objective function, which is constructed with the objective of minimizing the sum of squared errors between the sensor's measured propagation time and the theoretical propagation time. When the coordinate difference between two adjacent iterations of the objective function does not exceed the first target threshold, or the objective function value does not exceed the second target threshold, the target discharge coordinates of the discharge defect location are output.

7. The method according to claim 6, characterized in that, The iteration rules for the objective function include: The center point of the candidate region is selected as the initial iteration point, and the iteration step size is dynamically adjusted based on the target criterion. The dynamic adjustment rules include: if the objective function decreases after each iteration, the iteration step size is increased according to the first rule; if the objective function increases, the iteration step size is decreased according to the second rule.

8. A defect location device for high-voltage cables, characterized in that, include: The acquisition module is configured to acquire discharge signals corresponding to multiple sensors; The calculation module is configured to calculate the coarse time difference in the time domain and the fine time difference in the frequency domain for different discharge signals arriving at the corresponding sensor, and to perform weighted fusion of the coarse time difference in the time domain and the fine time difference in the frequency domain to obtain the target time difference; The positioning module is configured to determine the location of the discharge defect based on the target time difference, signal propagation speed, and coordinates of each sensor.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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