Interference compensation optimization method and system suitable for UHF partial discharge positioning of GIS cable terminal

Abstract

The invention provides an interference compensation optimization method and system suitable for UHF partial discharge positioning of a GIS cable terminal, and relates to the technical field of power equipment state monitoring. According to the method, a UHF sensor array layout mode is planned and customized, an acquisition system comprising a reference point layout module is built, a calibration waveform is obtained by using a portable PD simulator, and actually measured TDOA data is calculated by using a first peak detection method and is compared with theoretical TDOA to generate a systematic time difference compensation factor. After the TDOA data is compensated under the actual working condition, the corrected TDOA is input into an iterative optimization algorithm to solve the space coordinates of the partial discharge source, and high-precision positioning of partial discharge in the open environment is achieved.

Description

Technical Field

[0001] This invention relates to the field of power equipment condition monitoring technology, and in particular to an interference compensation optimization method and system suitable for UHF partial discharge location of GIS cable terminals. Background Technology

[0002] With the increasing demands for intelligence and reliability in power systems, partial discharge detection is playing an increasingly important role in the condition monitoring of GIS cable terminals. As a significant precursor to insulation degradation, accurate localization of partial discharge is crucial for preventing equipment failures and ensuring stable system operation. However, current UHF sensors are poorly adapted to GIS cable terminals; furthermore, in open substation environments, ubiquitous electromagnetic interference severely impacts the accuracy of partial discharge localization based on the time-of-arrival method, hindering its widespread application in practical engineering. Currently, partial discharge localization research largely focuses on ideal laboratory environments or simulation models. While these models can achieve high localization accuracy under interference-free conditions, they struggle to cope with the complex and variable electromagnetic environment of actual substations. Existing anti-interference methods often rely on signal post-processing algorithms or machine learning models, which are computationally complex, have slow response times, and require retraining or parameter adjustment in new environments, lacking dynamic adaptability to real-time interference. Furthermore, traditional methods generally neglect error compensation in the measurement process itself, resulting in large localization errors under strong interference environments, failing to meet the precise localization requirements of engineering projects.

[0003] The advantages and disadvantages of existing technologies are as follows: 1. There is a lack of UHF sensors suitable for GIS cable terminals. Furthermore, in the area of ​​partial discharge localization in open environments, most existing research methods are validated in controlled laboratory environments or simulation models. While these methods can achieve high positioning accuracy under interference-free conditions, they struggle to cope with the complex and variable electromagnetic interference environment near actual GIS cable terminals. These methods typically assume a relatively static measurement environment and fail to fully consider the impact of real-time electromagnetic interference on time difference of arrival (TDOA) measurements, leading to significantly increased positioning errors in real-world scenarios and severely limiting their engineering application value.

[0004] 2. Regarding anti-interference methods, existing technologies mostly rely on signal post-processing algorithms or complex machine learning models. While these methods can improve the signal-to-noise ratio under specific conditions, they are often computationally complex, have slow response times, and require retraining or parameter adjustment in new measurement environments, lacking real-time adaptability to dynamic interference. In particular, machine learning methods require a large amount of labeled data for model training, which not only increases system deployment costs but also makes it difficult to guarantee their generalization ability in different environments.

[0005] 3. Regarding sensor system deployment and calibration, existing partial discharge monitoring systems typically lack a rapid on-site calibration mechanism, making it impossible to calibrate the system in real time before measurement. Traditional calibration methods either rely on complex multi-day background measurements or completely ignore the influence of environmental interference, making it difficult for the system to adapt to changing interference conditions at different times and locations.

[0006] Currently, there is a lack of a comprehensive technical solution that can simultaneously address dynamic electromagnetic interference compensation, rapid on-site calibration, and efficient positioning calculation. This is of vital importance for improving the accuracy and reliability of partial discharge detection in GIS cable terminals and for promoting the in-depth application of condition-based maintenance technology in power systems. Summary of the Invention

[0007] To overcome the shortcomings of existing technologies, the purpose of this invention is to provide an interference compensation optimization method and system suitable for UHF partial discharge location of GIS cable terminals. By constructing a reference point calibration system, generating a systematic time difference compensation factor, and combining iterative optimization algorithms, high-precision location of partial discharge sources in GIS cable terminals in open environments is achieved using corrected TDOA data.

[0008] To achieve the above objectives, the present invention provides the following solution: An interference compensation optimization method for UHF partial discharge location of GIS cable terminals includes: Based on the interference characteristics of the open environment of GIS cable terminals and positioning requirements, a deployment method for a customized UHF sensor array is planned, and the time difference measurement accuracy target and anti-interference target of the customized UHF sensor array are defined. Based on the customized UHF sensor array deployment method, the customized UHF sensor array and high-speed acquisition system are built, and a replaceable reference point layout module is set up to deploy multiple reference points at known coordinate locations; the reference points are used to inject calibration pulses of analog PD signals to characterize open environment interference; After the customized UHF sensor array is fixedly deployed, a portable PD simulator is placed at each of the reference points in sequence to generate partial discharge simulation pulses. The high-speed acquisition system synchronously acquires the output of each UHF sensor channel in the customized UHF sensor array to obtain the sensor channel waveform data corresponding to each of the reference points. The first peak detection method is used to extract the signal arrival time of each UHF sensor from the waveform data of the sensor channel, and the measured TDOA data is calculated based on the arrival time of a preset reference sensor. Based on the coordinates of each reference point and the coordinates of each UHF sensor, theoretical TDOA data is calculated based on the electromagnetic wave propagation model at the speed of light. The theoretical TDOA data is compared with the measured TDOA data. The average time difference deviation corresponding to each reference point is calculated to obtain a systematic time difference compensation factor, and the systematic time difference compensation factor is stored. In the actual PD monitoring process, the customized UHF sensor array and the high-speed acquisition system are used to acquire the partial discharge signal waveform of the GIS cable terminal. The first peak detection method is used to calculate the measured TDOA data under the actual working conditions on the partial discharge signal waveform. The measured TDOA data under the actual working conditions is added to the systematic time difference compensation factor to obtain the corrected TDOA data. The corrected TDOA data is input into an iterative optimization algorithm, and the spatial coordinates of the partial discharge source are iteratively solved using the deviation between the corrected TDOA data and the theoretical TDOA data calculated from the spatial coordinates of the partial discharge source to be determined and the coordinates of the UHF sensor as the objective function.

[0009] Preferably, the customized UHF sensor array includes four identical UHF sensors arranged circumferentially along the GIS cable terminal. Each UHF sensor is based on a planar monopole antenna design, has an average realized gain of greater than 2dBi and a near-omnidirectional radiation mode in the operating frequency band of 0.3GHz to 3GHz, and the reflection coefficient of each UHF sensor is less than -10dB. It is self-powered and does not have a preamplifier.

[0010] Preferably, the high-speed acquisition system is a multi-channel high-speed oscilloscope with an analog bandwidth of not less than 2 GHz, and synchronously acquires the output of each UHF sensor channel in the customized UHF sensor array at a sampling rate of not less than 10 GS / s, so as to record the complete waveform details of the partial discharge simulation pulse and the actual partial discharge signal without distortion on the nanosecond time scale.

[0011] Preferably, the reference points are arranged radially along the GIS cable terminal within the space covered by the customized UHF sensor array. The coordinates of each reference point are determined by measurement, and the reference points used for calibration are excluded from the error statistics sample during the formal evaluation of positioning accuracy.

[0012] Preferably, the first peak detection method is: The time corresponding to the first peak point that significantly deviates from the background noise in the waveform data of each channel is identified and recorded as the signal arrival time of the corresponding UHF sensor; the peak point includes positive polarity peaks and negative polarity peaks; Using one of the UHF sensors as a preset reference sensor, the arrival time difference of the other UHF sensors relative to the preset reference sensor is calculated to obtain the measured TDOA data.

[0013] Preferably, the calculation steps for the theoretical TDOA data include: Calculate the Euclidean distance difference between each reference point and each UHF sensor based on the coordinates of each reference point and the coordinates of each UHF sensor; The Euclidean distance difference is normalized using the speed of light in air to obtain the theoretical time difference of arrival between each UHF sensor and the preset reference sensor under an ideal, interference-free environment. The systematic time difference compensation factor is the average value of the deviation between the theoretical TDOA data and the measured TDOA data for the same reference point and the same UHF sensor pair across all reference points, used to quantify the fixed time deviation introduced by environmental electromagnetic interference.

[0014] Preferably, in the actual PD monitoring process, the measured TDOA data under actual working conditions is the original time difference of arrival measurement value obtained by the first peak detection method from the multi-channel partial discharge signal waveform acquired by the high-speed acquisition system when a real partial discharge signal is detected; the corrected TDOA data is the result obtained by adding each of the original time difference of arrival measurement values ​​to the corresponding systematic time difference compensation factor one by one.

[0015] Preferably, the iterative optimization algorithm is a particle swarm optimization algorithm, with the sum of squares of the deviations between the corrected TDOA data and the theoretical TDOA data calculated from the spatial coordinates of the local discharge source and the coordinates of the UHF sensor as the objective function. By iteratively updating the position and velocity of the particle swarm, the objective function converges to the minimum value, thereby solving for the spatial coordinates of the local discharge source.

[0016] Preferably, considering the interference characteristics of the open environment of the GIS cable terminal and the positioning requirements, a customized UHF sensor array deployment method is planned, and the time difference measurement accuracy target and anti-interference target of the customized UHF sensor array are clearly defined, including: Based on the structural layout of GIS cable terminals and the interference characteristics of open environments, several candidate deployment methods for the customized UHF sensor array are set. Simulation positioning tests were conducted on each of the customized UHF sensor array deployment methods and different iterative optimization algorithms to obtain the corresponding time difference measurement error and anti-interference performance indicators. Based on the time difference measurement error and the anti-interference performance index, the deployment method and iterative optimization algorithm parameters of the customized UHF sensor array that meet the time difference measurement accuracy target and the anti-interference target are selected, thereby determining the deployment method of the customized UHF sensor array and determining the time difference measurement accuracy target and anti-interference target of the customized UHF sensor array.

[0017] An interference compensation and optimization system for UHF partial discharge location of GIS cable terminals includes: The UHF sensor array planning unit is used to plan the deployment method of a customized UHF sensor array by combining the interference characteristics of the open environment of the GIS cable terminal with the positioning requirements, and to clarify the time difference measurement accuracy target and anti-interference target of the customized UHF sensor array. The reference point layout and calibration pulse injection unit is used to complete the construction of the customized UHF sensor array and high-speed acquisition system based on the customized UHF sensor array layout method. It sets up a replaceable reference point layout module to lay out multiple reference points at known coordinate positions. The reference points are used to inject calibration pulses of analog PD signals to characterize open environment interference. The simulated partial discharge acquisition unit is used to place a portable PD simulator at each of the reference points in sequence after the customized UHF sensor array is fixedly deployed, generate simulated partial discharge pulses, and the high-speed acquisition system synchronously acquires the output of each UHF sensor channel in the customized UHF sensor array to obtain the sensor channel waveform data corresponding to each of the reference points. The arrival time extraction and measured TDOA calculation unit is used to extract the signal arrival time of each UHF sensor from the waveform data of the sensor channel using the first peak detection method, and calculate the measured TDOA data based on the arrival time of a preset reference sensor. The theoretical TDOA calculation and compensation factor generation unit is used to calculate theoretical TDOA data based on the coordinates of each reference point and the coordinates of each UHF sensor, using the electromagnetic wave propagation model at the speed of light, compare the theoretical TDOA data with the measured TDOA data, average the time difference deviations corresponding to each reference point to obtain a systematic time difference compensation factor, and store the systematic time difference compensation factor. The actual working condition TDOA correction unit is used to acquire the partial discharge signal waveform of the GIS cable terminal using the customized UHF sensor array and the high-speed acquisition system during the actual PD monitoring process, calculate the measured TDOA data under the actual working condition using the first peak detection method on the partial discharge signal waveform, and add the measured TDOA data under the actual working condition to the systematic time difference compensation factor to obtain the corrected TDOA data. The partial discharge source location solution unit is used to input the corrected TDOA data into an iterative optimization algorithm, and iteratively solve for the spatial coordinates of the partial discharge source using the deviation between the corrected TDOA data and the theoretical TDOA data calculated from the spatial coordinates of the partial discharge source to be determined and the coordinates of the UHF sensor as the objective function.

[0018] The present invention discloses the following technical effects: This invention plans a customized deployment method for a UHF sensor array based on the interference characteristics and positioning requirements of the open environment at GIS cable terminals, and clearly defines the time difference measurement accuracy and anti-interference targets. This avoids the problem of accumulated TDOA measurement deviations caused by the arbitrary sensor deployment and insufficient noise immunity in traditional partial discharge positioning methods. Because this invention takes into account both signal coverage characteristics and anti-interference requirements during the deployment stage, it can significantly improve the repeatability and stability of the original time of arrival measurement, providing an accurate foundation for subsequent positioning.

[0019] This invention utilizes a replaceable reference point layout module and deploys multiple reference points at known coordinate locations. By injecting simulated partial discharge pulses using a portable PD simulator, the system can actively construct a quantifiable calibration system in a real installation environment. Compared to prior art technologies that rely on laboratory pre-calibration or theoretical assumptions and fail to reflect changes in the field environment, this invention accurately acquires fixed errors introduced by systemic time delays, structural reflections, and multipath interference, thus laying the foundation for subsequent compensation.

[0020] This invention acquires sensor channel waveforms corresponding to each reference point and extracts the arrival time using the first peak detection method. It then calculates theoretical time-of-arrival (TDOA) data using an electromagnetic wave propagation model and generates a systematic time difference compensation factor based on the average deviation between the two methods. This effectively overcomes the limitation of traditional methods in quantifying time offsets caused by environmental interference. The compensated TDOA data significantly reduces error accumulation caused by environmental noise, structural reflections, and sensor response differences, improving the consistency and accuracy of the TDOA input data.

[0021] This invention employs the same time-of-arrival (TDOA) extraction method as the calibration phase during actual PD monitoring and compensates for the measured TDOA data under actual operating conditions, thereby ensuring high consistency of the positioning algorithm input data under field conditions. Compared to the instability of positioning results caused by changes in operating conditions (load, electromagnetic noise, attitude changes, etc.) in the prior art, this invention achieves dynamic adaptation to the actual operating environment, enabling the positioning results to maintain high accuracy and robustness under different operating conditions.

[0022] This invention modifies the iterative optimization algorithm for TDOA data input, using the minimization of the deviation between the corrected TDOA and the theoretical TDOA as the objective function, thereby achieving a high-precision solution for the spatial coordinates of local discharge sources. Compared to traditional positioning methods based on geometric inversion or simple least squares, which are susceptible to noise amplification and local extrema, the iterative optimization process employed in this invention can more effectively utilize the compensated high-quality data, improving convergence speed and positioning resolution, and enabling GIS cable terminal discharge positioning in open environments to achieve engineering-usable accuracy. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A flowchart illustrating the technical route provided in the embodiments of the present invention; Figure 2 This is a schematic diagram of the discharge signal provided in an embodiment of the present invention; Figure 3 A schematic diagram of voltage peak value provided for an embodiment of the present invention; Figure 4 This is a schematic diagram of the reference point location provided for an embodiment of the present invention. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] The purpose of this invention is to provide an interference compensation optimization method and system for UHF partial discharge location of GIS cable terminals. By utilizing a customized UHF sensor array, reference point calibration, and TDOA compensation mechanism, the accuracy of partial discharge signal arrival time extraction in complex environments of GIS cable terminals is improved, and the spatial accuracy of the partial discharge source is achieved through iterative optimization methods.

[0027] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0028] Figure 1 A flowchart illustrating the technical route provided in the embodiments of the present invention, such as... Figure 1 As shown, this invention provides an interference compensation optimization method suitable for UHF partial discharge location of GIS cable terminals, comprising: Step 100: Based on the interference characteristics of the open environment of the GIS cable terminal and the positioning requirements, plan the deployment method of the customized UHF sensor array, and clarify the time difference measurement accuracy target and anti-interference target of the customized UHF sensor array; Step 200: Based on the customized UHF sensor array deployment method, complete the construction of the customized UHF sensor array and high-speed acquisition system, set up a replaceable reference point layout module, and deploy multiple reference points at known coordinate locations; the reference points are used to inject calibration pulses of analog PD signals to characterize open environment interference; Step 300: After the customized UHF sensor array is fixedly deployed, the portable PD simulator is placed at each reference point in sequence to generate partial discharge simulation pulses. The high-speed acquisition system synchronously acquires the output of each UHF sensor channel in the customized UHF sensor array to obtain the sensor channel waveform data corresponding to each reference point. Step 400: Extract the signal arrival time of each UHF sensor from the waveform data of the sensor channel using the first peak detection method, and calculate the measured TDOA data based on the arrival time of the preset reference sensor. Step 500: Based on the coordinates of each reference point and the coordinates of each UHF sensor, calculate the theoretical TDOA data based on the electromagnetic wave propagation model at the speed of light. Compare the theoretical TDOA data with the measured TDOA data, average the time difference deviations corresponding to each reference point to obtain the systematic time difference compensation factor, and store the systematic time difference compensation factor. Step 600: In the actual PD monitoring process, the waveform of the partial discharge signal of the GIS cable terminal is obtained by using a customized UHF sensor array and a high-speed acquisition system. The first peak detection method is used to calculate the measured TDOA data under the actual working conditions. The measured TDOA data under the actual working conditions is added to the systematic time difference compensation factor to obtain the corrected TDOA data. Step 700: Input the corrected TDOA data into the iterative optimization algorithm, and use the deviation between the corrected TDOA data and the theoretical TDOA data calculated from the spatial coordinates of the partial discharge source and the coordinates of the UHF sensor as the objective function to iteratively solve for the spatial coordinates of the partial discharge source.

[0029] Figure 2This is a flowchart illustrating the interference compensation optimization method for UHF partial discharge location of GIS cable terminals according to the present invention. It sequentially shows the complete steps from planning and customizing the deployment of UHF sensor arrays, completing system construction, setting up calibration measurement points, collecting calibration data, calculating systematic time difference compensation factors, to achieving correction and positioning, and is used to explain the overall execution sequence of the method of the present invention.

[0030] The specific technical solution of this embodiment is as follows: (1) Sensor design: For GIS cable terminals, a UHF antenna is designed, and power supplies are randomly placed inside the GIS cable terminal. The sensitivity of the sensor to detect different discharge faults is tested. The average value of the measured discharge amount is used as the evaluation index. The position and size of the sensor are adjusted to obtain a sensor specifically for GIS cable terminals.

[0031] (2) System construction and algorithm pre-verification: The positioning method of this invention is based on a specially designed offline preparation and verification process. The core objective of this stage is to construct the hardware framework of the positioning system under ideal conditions that eliminate all interference from the real environment, and to verify and optimize the inherent performance of the core positioning algorithm, laying a solid foundation for its reliable application in complex field environments.

[0032] 1) Hardware system setup: Achieving high-precision partial discharge localization relies first and foremost on a stable and reliable hardware measurement system. In this invention, this system consists of three core units with clearly defined functions.

[0033] (a) UHF Sensor Array: Four identical UHF sensors are deployed around the GIS cable terminal, ensuring both functionality and cost-effectiveness while simplifying deployment. The sensors are based on a planar monopole antenna design, exhibiting an average realized gain exceeding 2 dBi and an omnidirectional radiation mode within the 0.3 GHz to 3 GHz operating frequency band, with a reflection coefficient below -10 dB, ensuring effective capture of wideband PD electromagnetic signals. These sensors are self-powered and amplifier-free, eliminating the complexity of external power supply and enhancing system portability.

[0034] The spatial coordinates of the sensors were precisely measured and fixed, and the layout of the sensor array was initially tested and optimized to provide strong angular coverage and consistent TDOA. Its geometry had to remain strictly unchanged throughout the experiment (including subsequent calibration and measurement), which was a prerequisite for effective compensation.

[0035] (b) Partial Discharge Source: This unit is a portable partial discharge simulator capable of generating standardized pulse signals with nanosecond-level rise times and consistent waveform characteristics. Its function is to simulate real partial discharges at known spatial locations during the calibration phase, such as a specific point on a GIS cable terminal, providing the system with a location-defined "truth" source. Results are as follows... Figure 3 As shown, a significant voltage peak appears on the nanosecond scale.

[0036] This source converts mechanical force into discharge through its piezoelectric element. Its portability and well-defined waveform characteristics make it an ideal reference source for controlled PD generation in experiments. The piezoelectric discharge source produces repeatable waveforms during repeated activation, demonstrating high measurement repeatability. This consistency allows for reliable evaluation of the localization algorithm under known true-ground conditions, ensuring that variations in localization results are attributable to algorithm performance and environmental factors, rather than source variability.

[0037] (c) Data Acquisition and Processing Unit: Data acquisition is performed by a multi-channel high-speed oscilloscope. The oscilloscope must have an analog bandwidth of no less than 2 GHz and simultaneously record the signal waveforms of all sensor channels at a sampling rate of no less than 10 GS / s to ensure that the high-frequency components of partial discharge can be captured without distortion.

[0038] Data processing is handled by a general-purpose computer that runs a customized positioning algorithm program. This program is responsible for performing signal processing, time difference extraction, and the final coordinate calculation.

[0039] 2) Establishment of simulation benchmarks and algorithm verification Once the hardware platform is determined, a pure, noise-free simulation environment needs to be established in the digital domain to verify the correctness and robustness of the positioning algorithm kernel. Perfectly ideal time difference of arrival (TDOA) data is generated as a "standard answer" for evaluating various solution algorithms, thus ensuring the mathematical rigor and solveability of the algorithm itself before introducing the complexities of the real world.

[0040] The simulation is strictly based on the principle of electromagnetic wave propagation at the speed of light in air. Input the pre-defined three-dimensional coordinates S of the sensor. i (x i ,y i ,z i And a large number of virtual partial discharge source coordinates P j (x j ,y j ,z j For each virtual power source P j Distance to each sensor D i It can be expressed by formula (1): (1) Choose any sensor as a reference (e.g., sensor 1), and use the known propagation speed of electromagnetic waves in air to calculate the theoretical arrival time difference between other sensors and the reference sensor, which can be expressed by formula (2): (2) in, c At the speed of light, T 1 The time it takes for the signal to reach sensor 1. T i For signal propagation to other sensors i The time required.

[0041] A set obtained from this t 21 , t 31 , t 41 This is an ideal TDOA dataset that is noise-free and interference-free. The large amount of ideal TDOA dataset generated above, covering the entire target space, is fed into candidate iterative optimization algorithms (particle swarm optimization) in batches. The task of each algorithm is to calculate the spatial coordinates of the discharge point based solely on the TDOA data and compare them with the preset "real" coordinates in the simulation.

[0042] In this ideal environment, systematic testing was conducted to evaluate the convergence success rate, positioning accuracy, and computational efficiency of each algorithm. Population size, number of iterations, and learning factor were adjusted to achieve near-perfect positioning performance under noise-free conditions.

[0043] The final output of this stage is a fully validated and optimized algorithm kernel and its parameter set, as well as a performance benchmark under ideal conditions.

[0044] (3) On-site dynamic calibration stage: 1) Artificial pulse injection and signal acquisition: Within the monitoring space covered by the sensor array, a set of pre-selected locations with precisely known spatial coordinates are used as reference points, such as... Figure 4 As shown (radial direction along the GIS cable terminal).

[0045] To ensure the fairness and accuracy of the evaluation, the reference points used in the calibration process should be excluded from the subsequent formal evaluation of the positioning accuracy of the method of the present invention and should not be used to calculate the final positioning error.

[0046] A portable partial discharge simulator is used, and it is placed sequentially at each of the aforementioned known reference locations. At each reference point, the simulator is operated to emit a standard, uniformly waveformd simulated partial discharge pulse. This pulse serves as the "real" signal, and the geometric location of its emission source is uniquely determined. With each artificial pulse emission, the system triggers a high-speed data acquisition unit (such as a multi-channel oscilloscope) to simultaneously record the signal waveforms received by all UHF sensors. The acquisition process must ensure a high sampling rate (e.g., 10 GS / s) and high bandwidth to accurately capture the complete details of the signal, especially its rising edge, laying the foundation for subsequent accurate time extraction.

[0047] 2) TDOA extraction and compensation factor calculation: This step is the core of the calibration process. By comparing the theoretical and measured values ​​of the known signal, the systematic error introduced by the environment is accurately calculated.

[0048] (a) Measurement and extraction of TDOA values: From the multi-channel waveform data acquired in step 1), the first peak detection method is used to extract the specific arrival time of the signal at each sensor. The first peak detection method identifies and records the time corresponding to the first peak point (whether positive or negative) in each channel waveform that significantly deviates from the background noise. This method is preferred due to its simple algorithm, low computational cost, and insensitivity to changes in the overall waveform shape. Using one sensor (e.g., sensor S1) as a unified reference, the measurement arrival time difference between the other sensors and this reference sensor is calculated and denoted as . t 21 measured , t 31 measured , t 41 measured .

[0049] (b) Calculation of theoretical TDOA value: For each reference position, based on its known three-dimensional coordinates and the fixed three-dimensional coordinates of all sensors, and using the physical model of electromagnetic waves propagating in a straight line at the speed of light, the theoretical distance from the reference point to each sensor is calculated. By calculating the difference between these theoretical distances and dividing by the speed of light, a set of theoretical arrival time differences is directly obtained, which can be expressed by formula (3): (3) in, d i and d j Reference position to sensor i and j Euclidean distance, cThis is the speed at which electromagnetic waves propagate in the air.

[0050] This set of data represents the time difference that should be measured under ideal, interference-free conditions.

[0051] (c) Calculation of compensation factor: Compare the theoretical TDOA value with the measured TDOA value for the same reference point and the same sensor pair. For each sensor pair (e.g., sensor...), i Compared with the reference sensor S1), its compensation factor The compensation factor is calculated by averaging the deviations observed at all reference points and can be expressed by formula (4): (4) in, k This represents the k-th reference position. The compensation factor quantitatively describes the fixed time deviation caused by environmental electromagnetic interference during the propagation of the electromagnetic wave signal from the discharge source to each UHF sensor. These deviations are not random noise, but rather stable and reproducible systematic errors that exist under specific measurement periods and sensor layouts. The calculated compensation factors for all sensor pairs (e.g., The data is stored in the system's processing unit for use during the real-time monitoring phase.

[0052] (4) Real-time monitoring and precise positioning stage 1) Real-time monitoring and error correction: When a real partial discharge signal is detected, its original, disturbed TDOA measurement value is extracted.

[0053] The original TDOA value is combined with the stored compensation factor to calculate the corrected TDOA value. The calculation method for the corrected value can be expressed by formula (5): (5) 2) PSO algorithm for localization: The corrected TDOA value is input into the iterative optimization algorithm to find the minimum value of the objective function, and finally the spatial coordinates of the PD source are calculated. f It can be calculated using formulas (6)-(9): (6) (7) (8) (9) in, r 1 Let be the difference between the distance from the PD source to sensor 2 and the distance to sensor 1. r2 The distances from the PD source to sensor 3 and to sensor 1 are the differences in distance. r 3 This represents the difference between the distance from the PD source to sensor 4 and the distance to sensor 1.

[0054] Preferably, the iterative optimization algorithm is a particle swarm optimization (PSO) algorithm, which iteratively updates the target value, converges to the optimal solution, and finally calculates the high-precision spatial coordinates of the local discharge source.

[0055] Corresponding to the above method, this embodiment also provides an interference compensation optimization system suitable for UHF partial discharge location of GIS cable terminals, including: The UHF sensor array planning unit is used to plan the deployment method of a customized UHF sensor array by combining the interference characteristics of the open environment of the GIS cable terminal with the positioning requirements, and to clarify the time difference measurement accuracy target and anti-interference target of the customized UHF sensor array. The reference point layout and calibration pulse injection unit is used to complete the construction of the customized UHF sensor array and high-speed acquisition system based on the customized UHF sensor array layout method. It sets up a replaceable reference point layout module to lay out multiple reference points at known coordinate positions. The reference points are used to inject calibration pulses of analog PD signals to characterize open environment interference. The simulated partial discharge acquisition unit is used to place a portable PD simulator at each of the reference points in sequence after the customized UHF sensor array is fixedly deployed, generate simulated partial discharge pulses, and the high-speed acquisition system synchronously acquires the output of each UHF sensor channel in the customized UHF sensor array to obtain the sensor channel waveform data corresponding to each of the reference points. The arrival time extraction and measured TDOA calculation unit is used to extract the signal arrival time of each UHF sensor from the waveform data of the sensor channel using the first peak detection method, and calculate the measured TDOA data based on the arrival time of a preset reference sensor. The theoretical TDOA calculation and compensation factor generation unit is used to calculate theoretical TDOA data based on the coordinates of each reference point and the coordinates of each UHF sensor, using the electromagnetic wave propagation model at the speed of light, compare the theoretical TDOA data with the measured TDOA data, average the time difference deviations corresponding to each reference point to obtain a systematic time difference compensation factor, and store the systematic time difference compensation factor. The actual working condition TDOA correction unit is used to acquire the partial discharge signal waveform of the GIS cable terminal using the customized UHF sensor array and the high-speed acquisition system during the actual PD monitoring process, calculate the measured TDOA data under the actual working condition using the first peak detection method on the partial discharge signal waveform, and add the measured TDOA data under the actual working condition to the systematic time difference compensation factor to obtain the corrected TDOA data. The partial discharge source location solution unit is used to input the corrected TDOA data into an iterative optimization algorithm, and iteratively solve for the spatial coordinates of the partial discharge source using the deviation between the corrected TDOA data and the theoretical TDOA data calculated from the spatial coordinates of the partial discharge source to be determined and the coordinates of the UHF sensor as the objective function.

[0056] The beneficial effects of this invention are as follows: This invention effectively suppresses the impact of electromagnetic interference on time difference positioning (TDOA) accuracy. Compared to traditional methods that rely on complex positioning algorithms or machine learning models for post-processing correction, this invention optimizes sensor design, performs on-site calibration before each measurement, acquires environmental interference characteristics, and dynamically compensates for TDOA measurements. Combined with optimized algorithms, it improves positioning accuracy, achieving high-precision positioning even in noisy environments. This method significantly improves the robustness and accuracy of partial discharge positioning, while also offering advantages such as high computational efficiency, simple deployment, and low cost. It is suitable for real-time monitoring and fault diagnosis in practical engineering scenarios such as substations.

[0057] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0058] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. An interference compensation optimization method for UHF partial discharge location of GIS cable terminals, characterized in that, include: Based on the interference characteristics of the open environment of GIS cable terminals and positioning requirements, a deployment method for a customized UHF sensor array is planned, and the time difference measurement accuracy target and anti-interference target of the customized UHF sensor array are defined. Based on the customized UHF sensor array deployment method, the customized UHF sensor array and high-speed acquisition system are built, and a replaceable reference point layout module is set up to deploy multiple reference points at known coordinate locations; the reference points are used to inject calibration pulses of analog PD signals to characterize open environment interference; After the customized UHF sensor array is fixedly deployed, a portable PD simulator is placed at each of the reference points in sequence to generate partial discharge simulation pulses. The high-speed acquisition system synchronously acquires the output of each UHF sensor channel in the customized UHF sensor array to obtain the sensor channel waveform data corresponding to each of the reference points. The first peak detection method is used to extract the signal arrival time of each UHF sensor from the waveform data of the sensor channel, and the measured TDOA data is calculated based on the arrival time of a preset reference sensor. Based on the coordinates of each reference point and the coordinates of each UHF sensor, theoretical TDOA data is calculated based on the electromagnetic wave propagation model at the speed of light. The theoretical TDOA data is compared with the measured TDOA data. The average time difference deviation corresponding to each reference point is calculated to obtain a systematic time difference compensation factor, and the systematic time difference compensation factor is stored. In the actual PD monitoring process, the customized UHF sensor array and the high-speed acquisition system are used to acquire the partial discharge signal waveform of the GIS cable terminal. The first peak detection method is used to calculate the measured TDOA data under the actual working conditions on the partial discharge signal waveform. The measured TDOA data under the actual working conditions is added to the systematic time difference compensation factor to obtain the corrected TDOA data. The corrected TDOA data is input into an iterative optimization algorithm, and the spatial coordinates of the partial discharge source are iteratively solved using the deviation between the corrected TDOA data and the theoretical TDOA data calculated from the spatial coordinates of the partial discharge source to be determined and the coordinates of the UHF sensor as the objective function.

2. The interference compensation optimization method for UHF partial discharge location of GIS cable terminals according to claim 1, characterized in that, The customized UHF sensor array includes four identical UHF sensors arranged circumferentially along the GIS cable terminal. Each UHF sensor is based on a planar monopole antenna design, has an average realized gain of greater than 2dBi and a near-omnidirectional radiation mode in the operating frequency band from 0.3GHz to 3GHz, and the reflection coefficient of each UHF sensor is less than -10dB. It is self-powered and does not have a preamplifier.

3. The interference compensation optimization method for UHF partial discharge location of GIS cable terminals according to claim 1, characterized in that, The high-speed acquisition system is a multi-channel high-speed oscilloscope with an analog bandwidth of no less than 2 GHz. It synchronously acquires the output of each UHF sensor channel in the customized UHF sensor array at a sampling rate of no less than 10 GS / s, so as to record the complete waveform details of the partial discharge simulation pulse and the actual partial discharge signal without distortion on the nanosecond time scale.

4. The interference compensation optimization method for UHF partial discharge location of GIS cable terminals according to claim 1, characterized in that, The reference points are arranged radially along the GIS cable terminal within the space covered by the customized UHF sensor array. The coordinates of each reference point are determined by measurement, and the reference points used for calibration are excluded from the error statistics sample during the formal evaluation of positioning accuracy.

5. The interference compensation optimization method for UHF partial discharge location of GIS cable terminals according to claim 1, characterized in that, The first peak detection method is: The time corresponding to the first peak point that significantly deviates from the background noise in the waveform data of each channel is identified and recorded as the signal arrival time of the corresponding UHF sensor; the peak point includes positive polarity peaks and negative polarity peaks; Using one of the UHF sensors as a preset reference sensor, the arrival time difference of the other UHF sensors relative to the preset reference sensor is calculated to obtain the measured TDOA data.

6. The interference compensation optimization method for UHF partial discharge location of GIS cable terminals according to claim 1, characterized in that, The calculation steps for the theoretical TDOA data include: Calculate the Euclidean distance difference from each reference point to each UHF sensor based on the coordinates of each reference point and the coordinates of each UHF sensor; The Euclidean distance difference is normalized using the speed of light in air to obtain the theoretical time difference of arrival between each UHF sensor and the preset reference sensor under an ideal, interference-free environment. The systematic time difference compensation factor is the average value of the deviation between the theoretical TDOA data and the measured TDOA data for the same reference point and the same UHF sensor pair across all reference points, used to quantify the fixed time deviation introduced by environmental electromagnetic interference.

7. The interference compensation optimization method for UHF partial discharge location of GIS cable terminals according to claim 1, characterized in that, In actual PD monitoring, the measured TDOA data under actual working conditions is the original time difference of arrival measurement value obtained by the first peak detection method from the multi-channel partial discharge signal waveform acquired by the high-speed acquisition system when a real partial discharge signal is detected. The corrected TDOA data is the result of adding each of the original time difference of arrival measurements to the corresponding systematic time difference compensation factor one by one.

8. The interference compensation optimization method for UHF partial discharge location of GIS cable terminals according to claim 1, characterized in that, The iterative optimization algorithm is a particle swarm optimization algorithm. The objective function is the sum of squares of the deviations between the corrected TDOA data and the theoretical TDOA data calculated from the spatial coordinates of the local discharge source and the coordinates of the UHF sensor. By iteratively updating the position and velocity of the particle swarm, the objective function converges to the minimum value, thereby solving for the spatial coordinates of the local discharge source.

9. The interference compensation optimization method for UHF partial discharge location of GIS cable terminals according to claim 1, characterized in that, Based on the interference characteristics of the open environment of GIS cable terminals and positioning requirements, a deployment method for a customized UHF sensor array is planned, and the time difference measurement accuracy target and anti-interference target of the customized UHF sensor array are defined, including: Based on the structural layout of GIS cable terminals and the interference characteristics of open environments, several candidate deployment methods for the customized UHF sensor array are set. Simulation positioning tests were conducted on each of the customized UHF sensor array deployment methods and different iterative optimization algorithms to obtain the corresponding time difference measurement error and anti-interference performance indicators. Based on the time difference measurement error and the anti-interference performance index, the deployment method and iterative optimization algorithm parameters of the customized UHF sensor array that meet the time difference measurement accuracy target and the anti-interference target are selected, thereby determining the deployment method of the customized UHF sensor array and determining the time difference measurement accuracy target and anti-interference target of the customized UHF sensor array.

10. An interference compensation and optimization system for UHF partial discharge location of GIS cable terminals, characterized in that, include: The UHF sensor array planning unit is used to plan the deployment method of a customized UHF sensor array by combining the interference characteristics of the open environment of the GIS cable terminal with the positioning requirements, and to clarify the time difference measurement accuracy target and anti-interference target of the customized UHF sensor array. The reference point layout and calibration pulse injection unit is used to complete the construction of the customized UHF sensor array and high-speed acquisition system based on the customized UHF sensor array layout method. It sets up a replaceable reference point layout module to lay out multiple reference points at known coordinate positions. The reference points are used to inject calibration pulses of analog PD signals to characterize open environment interference. The simulated partial discharge acquisition unit is used to place a portable PD simulator at each of the reference points in sequence after the customized UHF sensor array is fixedly deployed, generate simulated partial discharge pulses, and the high-speed acquisition system synchronously acquires the output of each UHF sensor channel in the customized UHF sensor array to obtain the sensor channel waveform data corresponding to each of the reference points. The arrival time extraction and measured TDOA calculation unit is used to extract the signal arrival time of each UHF sensor from the waveform data of the sensor channel using the first peak detection method, and calculate the measured TDOA data based on the arrival time of a preset reference sensor. The theoretical TDOA calculation and compensation factor generation unit is used to calculate theoretical TDOA data based on the coordinates of each reference point and the coordinates of each UHF sensor, using the electromagnetic wave propagation model at the speed of light, compare the theoretical TDOA data with the measured TDOA data, average the time difference deviations corresponding to each reference point to obtain a systematic time difference compensation factor, and store the systematic time difference compensation factor. The actual working condition TDOA correction unit is used to acquire the partial discharge signal waveform of the GIS cable terminal using the customized UHF sensor array and the high-speed acquisition system during the actual PD monitoring process, calculate the measured TDOA data under the actual working condition using the first peak detection method on the partial discharge signal waveform, and add the measured TDOA data under the actual working condition to the systematic time difference compensation factor to obtain the corrected TDOA data. The partial discharge source location solution unit is used to input the corrected TDOA data into an iterative optimization algorithm, and iteratively solve for the spatial coordinates of the partial discharge source using the deviation between the corrected TDOA data and the theoretical TDOA data calculated from the spatial coordinates of the partial discharge source to be determined and the coordinates of the UHF sensor as the objective function.

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