Anti-interference intelligent detection method and system for ultra-wideband partial discharge

Abstract

The present invention relates to the technical field of anti-interference detection, specifically including an anti-interference intelligent detection method and system for ultra-wideband partial discharge, comprising: obtaining partial discharge waveforms and interference signal waveforms respectively through synchronous trigger signals; after signal detection loss calibration, adopting an interference signal suppression strategy for comparison and suppression to obtain pure partial discharge waveforms, and calling a partial discharge diagnosis model to obtain a diagnosis result, solving the technical problem that in ultra-wideband partial discharge detection, the electromagnetic environment is complex and the frequency range of interference signals is wide, there is spectral overlap between interference signals and partial discharge signals, and it is difficult to meet the requirements of complex power equipment condition monitoring. It precisely calibrates the partial discharge waveforms, compensates for equipment losses and environmental impacts, and optimizes the detection strategy in real time according to signal characteristics, achieving the efficient separation of interference signals and partial discharge signals, dynamically adjusting during the detection process, and improving the purity of detection signals and the accuracy of analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of anti-interference detection, and particularly to an anti-interference intelligent detection method and system for ultra-wideband partial discharge. Background Art

[0002] Partial discharge detection is widely used in high-voltage power equipment such as transformers, cables, and switchgear. The monitoring of partial discharge signals can effectively reflect the internal insulation defects of the equipment, thus giving a warning before a fault occurs and ensuring the safe operation of the equipment. With the continuous expansion of the scale of the power system and the increase in equipment complexity, the requirements for the detection accuracy and reliability of partial discharge signals are gradually increasing.

[0003] Partial discharge signals are usually weak and mixed in complex background interference, and their anti-interference ability is limited. It is difficult to ensure the accuracy of the detection results, especially in a strong interference environment. At the same time, interference signals often overlap with partial discharge signals in terms of frequency, amplitude, and phase characteristics, further increasing the complexity of signal separation. The existing technologies for feature extraction and standardized diagnostic models of partial discharge cannot dynamically adapt to the changes in the equipment working environment and are difficult to meet the requirements of complex power equipment condition monitoring.

[0004] In summary, in the existing technology for ultra-wideband partial discharge detection, there are technical problems that the electromagnetic environment is complex, the frequency range of interference signals is wide, there is spectral overlap between interference signals and partial discharge signals, and it is difficult to meet the requirements of complex power equipment condition monitoring. Summary of the Invention

[0005] This application provides an anti-interference intelligent detection system for ultra-wideband partial discharge, aiming to solve the technical problems in the existing technology that in ultra-wideband partial discharge detection, the electromagnetic environment is complex, the frequency range of interference signals is wide, there is spectral overlap between interference signals and partial discharge signals, and it is difficult to meet the requirements of complex power equipment condition monitoring.

[0006] In view of the above problems, the technical solution of this application is as follows:

[0007] On the one hand, the present application provides an anti-interference intelligent detection method for ultra-wideband partial discharge. Among them, the method includes: obtaining an anti-interference detection device, where the anti-interference detection device includes a partial discharge detector and an interference detector; based on a synchronous trigger signal, respectively dynamically detecting a partial discharge waveform through the partial discharge detector and dynamically detecting an interference signal waveform through the interference detector, where the partial discharge waveform and the interference signal waveform conform to a predetermined synchronous constraint; introducing a signal detection loss calibration function to calibrate and analyze the partial discharge waveform to obtain an effective partial discharge waveform; reading an interference signal suppression strategy, and performing a comparison and suppression analysis on the effective partial discharge waveform and the interference signal waveform according to the interference signal suppression strategy to obtain a pure partial discharge waveform; retrieving a partial discharge diagnosis model to perform a diagnosis analysis on the pure partial discharge feature set of the pure partial discharge waveform to obtain a partial discharge diagnosis result.

[0008] Preferably, based on a synchronous trigger signal, respectively dynamically detecting a partial discharge waveform through the partial discharge detector and dynamically detecting an interference signal waveform through the interference detector includes: establishing a fully shielded space, and arranging a predetermined high-voltage power supply in the fully shielded space; under a predetermined detection constraint, applying pressure to a target ultra-wideband through the predetermined high-voltage power supply, and detecting signals of the pressurized target ultra-wideband through a detector to obtain an initial signal waveform; where the initial signal waveform includes an initial partial discharge waveform dynamically detected by the partial discharge detector in the detector and an initial interference waveform dynamically detected by the interference detector in the detector; recording the conditioning of the initial partial discharge waveform and the initial interference waveform based on a signal conditioning strategy through a digital oscilloscope to respectively obtain a partial discharge waveform and an interference signal waveform.

[0009] Preferably, the predetermined detection constraint includes a temperature constraint, a humidity constraint, and an interference level constraint.

[0010] Preferably, the partial discharge detector refers to a matching impedance sampler established based on the matching impedance principle, and the interference detector refers to a microstrip coupling sampler established based on a microstrip coupling antenna sensor.

[0011] Preferably, the expression of the signal detection loss calibration function is as follows:

[0012] ; where refers to the partial discharge waveform between the and the effective partial discharge waveform is the signal detection loss calibration function between them, is the device loss calibration coefficient of the target ultra-wideband, refers to a predetermined attenuation factor, and .

[0013] Preferably, it further includes: obtaining a partial discharge detection sample; detecting the partial discharge detection sample through the partial discharge detector to obtain a partial discharge waveform under air; placing the partial discharge detection sample in insulating oil, and detecting the partial discharge detection sample through the partial discharge detector to obtain a partial discharge waveform under insulating oil; comparing the partial discharge waveform under air with the partial discharge waveform under insulating oil to obtain a waveform deviation; performing weighted calculation on the deviation characteristic parameter set of the waveform deviation after normalization processing to obtain the predetermined attenuation factor .

[0014] Preferably, the deviation characteristic parameter set at least includes an amplitude deviation parameter and a phase deviation parameter.

[0015] Preferably, reading an interference signal suppression strategy, and performing comparative suppression analysis on the effective partial discharge waveform and the interference signal waveform according to the interference signal suppression strategy to obtain a pure partial discharge waveform, including: estimating Fourier series coefficients based on the Fourier series method, and using the Fourier series coefficients to obtain an estimated interference waveform; adjusting the interference signal waveform with the estimated interference waveform according to the interference signal suppression strategy to obtain an effective interference waveform; subtracting and canceling the effective partial discharge waveform and the effective interference waveform to obtain the pure partial discharge waveform.

[0016] Preferably, invoking a partial discharge diagnosis model to perform diagnostic analysis on the pure partial discharge feature set of the pure partial discharge waveform to obtain a partial discharge diagnosis result, including: obtaining a historical partial discharge log of the target ultra-wideband; extracting a first partial discharge record from the historical partial discharge log, the first partial discharge record including a first pure partial discharge waveform and a first partial discharge type; constructing a first data set based on the first waveform feature of the first pure partial discharge waveform and the first partial discharge type, and performing supervised learning on the first data set to obtain the partial discharge diagnosis model.

[0017] On the other hand, the present application provides an anti-interference intelligent detection system for ultra-wideband partial discharge. Among them, the system includes: a detection module for obtaining an anti-interference detection device, which includes a partial discharge detector and an interference detector; a dynamic detection module for dynamically detecting a partial discharge waveform through the partial discharge detector and an interference signal waveform through the interference detector based on a synchronous trigger signal, where the partial discharge waveform and the interference signal waveform conform to a predetermined synchronous constraint; a calibration analysis module for introducing a signal detection loss calibration function to calibrate and analyze the partial discharge waveform to obtain an effective partial discharge waveform; a suppression analysis module for reading an interference signal suppression strategy and performing a comparison and suppression analysis on the effective partial discharge waveform and the interference signal waveform according to the interference signal suppression strategy to obtain a pure partial discharge waveform; and a diagnosis analysis module for retrieving a partial discharge diagnosis model to perform a diagnosis analysis on the pure partial discharge feature set of the pure partial discharge waveform to obtain a partial discharge diagnosis result.

[0018] In summary, one or more technical solutions provided in the present application, through the combined dynamic detection of an interference detector and a partial discharge detector, and the time constraint of a synchronous trigger signal, accurately calibrate the partial discharge waveform, compensate for equipment losses and environmental impacts, and optimize the detection strategy in real time according to signal characteristics, achieving the technical effects of efficient separation of interference signals and partial discharge signals, dynamic adjustment during the detection process, and improving the purity of detection signals and the accuracy of analysis. Description of the Drawings

[0019] Figure 1 It is a schematic flowchart of an anti-interference intelligent detection method for ultra-wideband partial discharge provided by the present application;

[0020] Figure 2 It is a schematic structural diagram of an anti-interference intelligent detection system for ultra-wideband partial discharge provided by the present application.

[0021] Description of the reference numerals: detection module M100, dynamic detection module M200, calibration analysis module M300, suppression analysis module M400, diagnosis analysis module M500. Detailed Description of the Embodiments Embodiment 1

[0022] The present application will be specifically described below with reference to the drawings. As Figure 1 shown, the present application provides an anti-interference intelligent detection method for ultra-wideband partial discharge. Among them, the method includes:

[0023] S1: Obtain an anti-interference detection device, where the anti-interference detection device includes a partial discharge detector and an interference detector; S2: Based on a synchronous trigger signal, dynamically detect a partial discharge waveform through the partial discharge detector and dynamically detect an interference signal waveform through the interference detector, where the partial discharge waveform and the interference signal waveform comply with a predetermined synchronous constraint.

[0024] Specifically, the anti-interference detection device is used to detect partial discharge signals in a complex electromagnetic environment, including a partial discharge detector and an interference detector. The partial discharge detector is a sensor used to capture the electrical signals generated by partial discharge events, and the interference detector is used to identify and measure external interference signals that may affect the partial discharge signals. Through the cooperation between the partial discharge detector and the interference detector, the influence of external interference on the detection results is reduced or eliminated; the synchronous trigger signal is used to ensure that the partial discharge detector and the interference detector can collect signals at the same moment or at a predetermined time interval, thereby ensuring the time synchronization between the partial discharge waveform and the interference signal waveform.

[0025] Deploy the anti-interference detection device, including installing and calibrating the partial discharge detector and the interference detector. The partial discharge detector is usually placed near high-voltage power equipment so as to be able to capture the weak signals generated by partial discharge events; the interference detector is used to monitor possible interference sources in the surrounding environment, such as electromagnetic interference, radio waves, etc.; through the synchronous trigger signal, the partial discharge detector and the interference detector can collect signals at the same time point or at a predetermined time interval, thereby obtaining the partial discharge waveform and the interference signal waveform. In this way, the partial discharge detector and the interference detector cooperate with each other. For example, during the maintenance of a high-voltage transformer, the partial discharge detector is installed on the tank wall of the transformer, and the interference detector is installed on the ground around the transformer. By using the synchronous trigger signal, when a partial discharge occurs inside the transformer, the partial discharge detector will capture the partial discharge waveform, and the interference detector will capture the interference signal waveform at the same moment.

[0026] S3: Introduce a signal detection loss calibration function to calibrate and analyze the partial discharge waveform to obtain an effective partial discharge waveform; S4: Read the interference signal suppression strategy, and perform a comparison and suppression analysis on the effective partial discharge waveform and the interference signal waveform according to the interference signal suppression strategy to obtain a pure partial discharge waveform; S5: Invoke the partial discharge diagnosis model to perform a diagnosis analysis on the pure partial discharge feature set of the pure partial discharge waveform to obtain a partial discharge diagnosis result.

[0027] Specifically, the signal detection loss calibration function is used to correct the distortion in the partial discharge waveform caused by factors such as equipment performance loss and signal attenuation. By adjusting the waveform data, these losses are compensated to obtain a more accurate representation of the partial discharge signal. The interference signal suppression strategy is used to reduce or eliminate the impact of interference signals on the partial discharge waveform, including filtering, signal cancellation, or other signal processing techniques. The purpose is to extract a pure partial discharge waveform from the mixed signal. The partial discharge diagnosis model is used to analyze the characteristics of the pure partial discharge waveform, identify the relationship between different partial discharge characteristics and specific fault types, and diagnose the type and severity of partial discharge accordingly.

[0028] Analyze the captured partial discharge waveform using the signal detection loss calibration function, considering the equipment loss calibration coefficient and the predetermined attenuation factor , adjust the waveform data to compensate for the losses during signal transmission and detection, ensuring the accuracy of the partial discharge waveform. According to the read interference signal suppression strategy, conduct a comparative analysis of the calibrated effective partial discharge waveform and the interference signal waveform, effectively separating the partial discharge signal and the interference signal, improving the accuracy and reliability of partial discharge detection, providing a clear signal basis for partial discharge diagnosis. Further, use the partial discharge diagnosis model to analyze the feature set of the pure partial discharge waveform, including extracting waveform features such as amplitude, frequency, phase, etc., and using these features to diagnose the fault type and severity.

[0029] Specifically, the signal detection loss calibration function includes gain adjustment and filtering processing of the partial discharge waveform to compensate for the attenuation of the cable and sensor. The interference signal suppression strategy includes using a band-stop filter to reduce interference at specific frequencies, or using adaptive filtering techniques to dynamically adjust the filtering parameters to adapt to the changing interference environment. The partial discharge diagnosis model is trained based on empirical data and can identify the association between specific waveform features and fault types. For example, discharges in oil-paper insulation usually exhibit a specific frequency distribution. Through these steps, rapid and accurate diagnosis of partial discharge events is achieved, thereby early warning of potential equipment failures and making the detection results more reliable.

[0030] Furthermore, based on the synchronous trigger signal, the partial discharge waveform is dynamically detected by the partial discharge detector respectively, and the interference signal waveform is dynamically detected by the interference detector. The method of the present application includes:

[0031] Establish a fully shielded space and deploy a predetermined high-voltage power supply in the fully shielded space; under predetermined detection constraints, apply pressure to the target ultra-wideband through the predetermined high-voltage power supply, and detect the signals of the target ultra-wideband under pressure through a detector to obtain an initial signal waveform; wherein, the initial signal waveform includes an initial partial discharge waveform dynamically detected by the partial discharge detector in the detector and an initial interference waveform dynamically detected by the interference detector in the detector; record the conditioning of the initial partial discharge waveform and the initial interference waveform based on a signal conditioning strategy through a digital oscilloscope to obtain a partial discharge waveform and an interference signal waveform respectively.

[0032] Specifically, the fully shielded space is used to isolate the external electromagnetic interference environment, usually composed of metal or other shielding materials, which can block the entry of external electromagnetic waves and provide a clean test environment for partial discharge detection; the predetermined high-voltage power supply is a power supply device set in the fully shielded space, used to apply high voltage to the target ultra-wideband device to simulate the power equipment under actual working conditions, so as to induce partial discharge phenomena; the predetermined detection constraints refer to a series of conditions that need to be observed during partial discharge detection, such as temperature, humidity, and interference level, etc., which ensure the consistency and reliability of the test; the signal conditioning strategy is used to optimize and condition the initial signal waveform, including amplification, filtering, and impedance matching, to improve the signal quality and reduce noise interference, so as to facilitate more accurate analysis and identification of partial discharge waveforms and interference signal waveforms.

[0033] Establish a fully shielded space, which is composed of metal or other electromagnetic shielding materials to isolate external electromagnetic interference; inside the fully shielded space, deploy a predetermined high-voltage power supply for applying high voltage to the target ultra-wideband device; through the above steps, a non-interference environment is provided for partial discharge detection, ensuring the accuracy and reliability of the detection results.

[0034] Inside the fully shielded space, apply high voltage to the target ultra-wideband device through a predetermined high-voltage power supply to simulate actual working conditions. At the same time, use a partial discharge detector and an interference detector to detect the signals of the target device under pressure to obtain an initial signal waveform; in the above steps, by simulating actual working conditions, partial discharge phenomena are induced, and at the same time, partial discharge waveforms and interference signal waveforms are captured, providing basic data for subsequent signal analysis.

[0035] Use a digital oscilloscope to perform signal conditioning on the initial partial discharge waveform and the initial interference waveform, such as filtering, amplification, etc., optimize and adjust the waveform according to the signal conditioning strategy, and record the conditioned waveform data. In the above steps, the quality of the waveform data is improved through the signal conditioning strategy, making the partial discharge waveform and the interference signal waveform easier to be identified and analyzed, providing a data basis for subsequent signal separation and diagnosis.

[0036] Furthermore, the method of the present application includes:

[0037] The predetermined detection constraints include temperature constraints, humidity constraints, and interference level constraints.

[0038] Specifically, the temperature constraint refers to the control requirements for the ambient or equipment temperature during partial discharge detection. The change in temperature will affect the characteristics of the partial discharge signal, such as the signal propagation speed and amplitude. The humidity constraint is an environmental factor affecting partial discharge detection. The level of humidity can affect the performance of insulating materials and the propagation of partial discharge signals. Therefore, it is necessary to control the ambient humidity during the detection process. The interference level constraint refers to the limitation of the intensity of possible external electromagnetic interference during partial discharge detection. To ensure the accuracy of the detection results, it is necessary to control the interference level within a predetermined range to reduce the impact on the detection signal.

[0039] During partial discharge detection, it is necessary to operate under the predetermined detection constraints. Specifically, the temperature constraint (such as 20°C ± 2°C) is used to ensure that the temperature of the detection environment or equipment is maintained within a certain range, which involves using a constant temperature device or selecting to conduct tests under specific temperature conditions. The humidity constraint (such as 45% ± 5%) is used to control the humidity of the detection environment, and it may be necessary to use a dehumidifier or a humidifier to adjust the ambient humidity. The interference level constraint is used to reduce the external electromagnetic interference to a level below the predetermined level through measures such as using shielding devices, selecting appropriate test times and locations, etc., to ensure the consistency and controllability of the detection conditions, thereby improving the accuracy and reliability of the detection results. By controlling the environmental factors, the influence of external variables on the detection results can be reduced, making the detection data more stable and reliable.

[0040] Furthermore, the method of the present application includes:

[0041] The partial discharge detector refers to a matching impedance sampler established based on the principle of matching impedance, and the interference detector refers to a microstrip coupled sampler established based on a microstrip coupled antenna sensor.

[0042] Specifically, the matching impedance means that the load impedance is equal to the source impedance to achieve maximum power transfer. In partial discharge detection, the matching impedance sampler can ensure the maximization of the signal transmission efficiency from the detection point to the detection device and reduce signal loss. The microstrip coupled antenna sensor is constructed based on microstrip line technology. A microstrip line is a transmission line structure composed of a conductor strip and a ground plane, usually used in the microwave frequency range. The microstrip coupled antenna sensor utilizes the characteristics of the microstrip line to detect and measure interference signals. The microstrip coupled sampler is used to couple signals from the microstrip line to detect and analyze interference signals.

[0043] The partial discharge detector refers to a matching impedance sampler based on the principle of matching impedance, which ensures that the signal loss is minimized during the signal transmission process from the device under test to the detector. It usually includes a circuit that matches the impedance of the device under test to achieve efficient signal transmission and reception. The interference detector uses microstrip line technology to detect interference signals in the environment. The interference signals captured by the microstrip coupled antenna sensor are coupled and transmitted through the microstrip coupled sampler for further analysis and processing. Preferably, the partial discharge detector improves the signal transmission efficiency and reduces signal loss through the principle of matching impedance, thereby improving the detection accuracy of partial discharge signals. The interference detector can effectively capture and measure interference signals through microstrip coupling technology, providing a basis for subsequent signal processing and analysis.

[0044] Furthermore, the method of the present application includes:

[0045] The expression of the signal detection loss calibration function is as follows: ; where refers to the partial discharge waveform and the effective partial discharge waveform between the signal detection loss calibration function, refers to the device loss calibration coefficient of the target ultra-wideband, refers to the performance loss calibration coefficient of the partial discharge detector, refers to the predetermined attenuation factor, and .

[0046] Specifically, the signal detection loss calibration function is , where refers to the device loss calibration coefficient of the target ultra-wideband, which reflects the loss of the signal by the device itself, refers to the performance loss calibration coefficient of the partial discharge detector, such as sensitivity and frequency response, which reflects the loss of the signal during the detection process and the loss of the detector to the signal, and describes the attenuation degree of the signal with frequency; refers to the predetermined attenuation factor, which describes the attenuation degree of the signal with frequency. During the signal transmission process, high-frequency signals usually attenuate faster than low-frequency signals. The predetermined attenuation factor is used to correct this frequency-dependent attenuation.

[0047] In the calibration analysis of the partial discharge waveform, the signal detection loss calibration function is used to adjust the waveform data to improve the accuracy of the partial discharge waveform. By correcting the loss in the signal detection process to compensate for the signal loss, the original waveform of the partial discharge is more accurately restored, providing a high-quality data basis for subsequent signal analysis and fault diagnosis.

[0048] Furthermore, the method of the present application also includes:

[0049] Obtain a partial discharge detection specimen; detect the partial discharge detection specimen through the partial discharge detector to obtain a partial discharge waveform under air; place the partial discharge detection specimen in insulating oil, and detect the partial discharge detection specimen through the partial discharge detector to obtain a partial discharge waveform under insulating oil; compare the partial discharge waveform under air with the partial discharge waveform under insulating oil to obtain a waveform deviation; perform weighted calculation on the deviation characteristic parameter set of the waveform deviation after normalization processing to obtain the predetermined attenuation factor 。

[0050] Specifically, the partial discharge detection specimen refers to a sample used for partial discharge detection, which can be a part of a power equipment, such as a cable, insulating material, etc., and is used to simulate the partial discharge phenomenon under actual working conditions under predetermined detection constraints; the partial discharge waveform under air refers to the waveform data obtained when the partial discharge detection specimen is subjected to partial discharge detection in air, reflecting the partial discharge characteristics without the influence of other media; the partial discharge waveform under insulating oil refers to the waveform data obtained when the partial discharge detection specimen is placed in insulating oil for partial discharge detection. Insulating oil is a commonly used liquid insulating material, and its characteristics are different from those of air, which will affect the propagation of partial discharge signals; the waveform deviation refers to the difference between the partial discharge waveform under air and the partial discharge waveform under insulating oil, and the waveform deviation provides information about the change in discharge characteristics of the partial discharge detection specimen in different media; the deviation characteristic parameter set refers to a set of key parameters extracted from the waveform deviation, such as amplitude deviation, phase deviation, etc., which can characterize the difference between waveforms.

[0051] Obtain or prepare specimens for partial discharge detection, and these specimens should be able to represent the insulating materials or structures in actual power equipment; place the partial discharge detection specimen in air, use a partial discharge detector to detect it, and record the waveform data generated by partial discharge events; place the partial discharge detection specimen in insulating oil, and use the partial discharge detector again for detection, and record the waveform data of partial discharge events in insulating oil. Further, compare the partial discharge waveforms under air and under insulating oil, analyze the differences between the two, and obtain a waveform deviation; extract key deviation characteristic parameters from the waveform deviation, such as amplitude deviation and phase deviation; perform normalization processing on the extracted deviation characteristic parameter set, and obtain the predetermined attenuation factor through weighted calculation for calibrating the partial discharge detection signal of an actual cable during operation to compensate for the signal attenuation caused by the change of the medium, thereby improving the accuracy and reliability of detection. In the above steps, by comparing the differences in partial discharge waveforms under different media, the performance changes of the partial discharge detection specimen under actual working conditions are evaluated, and the partial discharge behavior of actual power equipment under different environments is more accurately simulated and predicted.

[0052] Furthermore, the method of the present application includes:

[0053] The deviation characteristic parameter set at least includes an amplitude deviation parameter and a phase deviation parameter.

[0054] Specifically, the amplitude deviation parameter is a parameter that describes the amplitude change of the partial discharge waveform in different media (such as air and insulating oil), reflecting the change in the intensity of the partial discharge signal; the phase deviation parameter is a parameter for the phase change of the partial discharge waveform in different media, reflecting the time delay or advance of the partial discharge signal during propagation, and is used to analyze the signal propagation characteristics and the influence of the medium.

[0055] When comparing the partial discharge waveform in air with that in insulating oil, measure and record the amplitude difference between the two waveforms, which reflects the propagation characteristics and attenuation of the partial discharge signal in different media. Similarly, when comparing the two waveforms, measure and record the phase difference between the two waveforms to reveal the propagation speed and path change of the partial discharge signal in different media; combine the extracted amplitude deviation parameter and phase deviation parameter to construct a deviation characteristic parameter set; the propagation of the partial discharge signal in insulating oil is affected by attenuation and phase delay. By incorporating these parameters into the deviation characteristic parameter set and performing weighted calculation, a predetermined attenuation factor is obtained, which is used to calibrate the partial discharge detection signal of the actual cable in different media, improving the accuracy and reliability of the detection. In the above steps, by quantitatively analyzing the changes of the partial discharge waveform in different media, key data for signal calibration and fault diagnosis are provided; the deviation parameters of amplitude and phase are used to evaluate the partial discharge characteristics and the influence of the medium, which helps to more accurately understand and predict the partial discharge behavior.

[0056] Furthermore, read the interference signal suppression strategy, and perform comparative suppression analysis on the effective partial discharge waveform and the interference signal waveform according to the interference signal suppression strategy to obtain a pure partial discharge waveform. The method of the present application includes:

[0057] Estimate the Fourier series coefficients based on the Fourier series method, and use the Fourier series coefficients to obtain an estimated interference waveform; according to the interference signal suppression strategy, adjust the interference signal waveform with the estimated interference waveform to obtain an effective interference waveform; subtract and cancel the effective partial discharge waveform and the effective interference waveform to obtain the pure partial discharge waveform.

[0058] Specifically, the Fourier series method is used to represent a periodic function as a sum of sine and cosine functions. In signal processing, the Fourier series method can be used to decompose complex signal waveforms and extract their frequency components; the Fourier series coefficients are the coefficients in the Fourier series expansion, which determine the amplitudes and phases of the individual sine and cosine terms, thus enabling the reconstruction of the original signal; the estimated interference waveform is the interference signal waveform reconstructed based on the Fourier series coefficients and is used for subsequent interference signal suppression; the effective interference waveform is the interference waveform adjusted according to the interference signal suppression strategy, which is closer to the actual interference signal and can be used to subtract from the partial discharge waveform; subtraction cancellation refers to eliminating the common part by subtracting two waveforms to separate the desired signal.

[0059] Apply the Fourier series method to the collected interference signal waveform to estimate the Fourier series coefficients describing the waveform; use the estimated Fourier series coefficients to reconstruct the interference signal waveform, which is an approximate representation of the actual interference signal; adjust based on the estimated interference waveform according to a pre-set interference signal suppression strategy to obtain an effective interference waveform closer to the actual interference signal; subtract the effective partial discharge waveform from the effective interference waveform to cancel the influence of the interference signal and obtain a pure partial discharge waveform. In the above steps, through precise signal processing techniques, a pure partial discharge signal is separated from the mixed signal, the interference waveform is estimated and adjusted, effectively reducing the influence of the interference signal on the partial discharge signal, accurately analyzing and diagnosing the partial discharge situation of the transformer, thereby improving the accuracy and reliability of partial discharge detection.

[0060] Furthermore, retrieve the partial discharge diagnosis model to perform diagnostic analysis on the pure partial discharge feature set of the pure partial discharge waveform to obtain a partial discharge diagnosis result. The method of this application includes:

[0061] Obtain the historical partial discharge log of the target ultra-wideband; extract the first partial discharge record from the historical partial discharge log, where the first partial discharge record includes the first pure partial discharge waveform and the first partial discharge type; form a first data set based on the first waveform feature of the first pure partial discharge waveform and the first partial discharge type, and perform supervised learning on the first data set to obtain the partial discharge diagnosis model.

[0062] Specifically, the historical partial discharge log refers to a log file that records past partial discharge events occurring in a specific device or system, containing detailed information about each partial discharge event, such as time, location, waveform data, and type, etc.; the first partial discharge record is the record of a single partial discharge event extracted from the historical partial discharge log, including the pure partial discharge waveform and the partial discharge type of the event; the first waveform feature refers to the key features extracted from the first pure partial discharge waveform, which can characterize the characteristics of the partial discharge event, such as the amplitude, frequency, and duration of the waveform.

[0063] Supervised learning learns from labeled training data, where each training sample contains input data and corresponding output labels. Specifically, supervised learning is used to train a model to recognize the relationship between specific partial discharge waveform features and partial discharge types; obtain the historical partial discharge logs of the target ultra-wideband device, where the historical partial discharge logs record all past partial discharge events; extract the first partial discharge record from the historical partial discharge logs, and the first partial discharge record includes the pure partial discharge waveform of the event and the known partial discharge type; based on the first waveform features (such as amplitude, frequency, and phase) of the extracted first pure partial discharge waveform and the corresponding partial discharge type (for example, corona discharge or spark discharge), construct a first data set, and the first data set is used to train the partial discharge diagnosis model; use the constructed first data set to perform supervised learning on the partial discharge diagnosis model, and learn how to identify and classify different partial discharge events by analyzing the relationship between waveform features and partial discharge types. By constructing a partial discharge diagnosis model through supervised learning, the partial discharge diagnosis model learns the association between the features of partial discharge waveforms and partial discharge types from historical data, so that when a new partial discharge event occurs, it analyzes its waveform features and predicts the partial discharge type, providing a fast and accurate diagnosis.

[0064] In summary, the beneficial effects of the embodiments of the present application are:

[0065] Since an anti-interference detection device is adopted, the anti-interference detection device includes a partial discharge detector and an interference detector; based on a synchronous trigger signal, a partial discharge waveform is dynamically detected by the partial discharge detector, and an interference signal waveform is dynamically detected by the interference detector, where the partial discharge waveform and the interference signal waveform conform to a predetermined synchronous constraint; a signal detection loss calibration function is introduced to calibrate and analyze the partial discharge waveform to obtain an effective partial discharge waveform; read the interference signal suppression strategy, and perform comparative suppression analysis on the effective partial discharge waveform and the interference signal waveform according to the interference signal suppression strategy to obtain a pure partial discharge waveform; retrieve the partial discharge diagnosis model to perform diagnostic analysis on the pure partial discharge feature set of the pure partial discharge waveform to obtain a partial discharge diagnosis result. The present application provides an anti-interference intelligent detection method for ultra-wideband partial discharge, accurately calibrates the partial discharge waveform, compensates for equipment losses and environmental impacts, optimizes the detection strategy in real time according to signal characteristics, realizes the efficient separation of interference signals and partial discharge signals, dynamically adjusts during the detection process, and improves the purity of the detection signal and the technical effect of analysis accuracy. Embodiment 2

[0066] Based on the same inventive concept as the anti-interference intelligent detection method for ultra-wideband partial discharge in the foregoing embodiment, as Figure 2 shown, the embodiments of the present application provide an anti-interference intelligent detection system for ultra-wideband partial discharge, where the system includes:

[0067] Detection module M100, configured to obtain an anti-interference detection device, where the anti-interference detection device includes a partial discharge detector and an interference detector;

[0068] Dynamic detection module M200, configured to, based on a synchronous trigger signal, dynamically detect a partial discharge waveform through the partial discharge detector and dynamically detect an interference signal waveform through the interference detector, where the partial discharge waveform and the interference signal waveform conform to a predetermined synchronous constraint;

[0069] Calibration and analysis module M300, configured to introduce a signal detection loss calibration function to calibrate and analyze the partial discharge waveform to obtain an effective partial discharge waveform;

[0070] Suppression and analysis module M400, configured to read an interference signal suppression strategy and perform a comparison and suppression analysis on the effective partial discharge waveform and the interference signal waveform according to the interference signal suppression strategy to obtain a pure partial discharge waveform;

[0071] Diagnosis and analysis module M500, configured to retrieve a partial discharge diagnosis model to perform a diagnosis and analysis on the pure partial discharge feature set of the pure partial discharge waveform to obtain a partial discharge diagnosis result.

[0072] Further, the dynamic detection module M200 is configured to execute the following method:

[0073] Establish a fully shielded space and deploy a predetermined high-voltage power supply in the fully shielded space;

[0074] Under a predetermined detection constraint, apply pressure to a target ultra-wideband through the predetermined high-voltage power supply and perform signal detection on the pressurized target ultra-wideband through a detector to obtain an initial signal waveform;

[0075] Wherein, the initial signal waveform includes an initial partial discharge waveform dynamically detected by the partial discharge detector in the detector and an initial interference waveform dynamically detected by the interference detector in the detector;

[0076] Record the conditioning of the initial partial discharge waveform and the initial interference waveform based on a signal conditioning strategy through a digital oscilloscope to obtain a partial discharge waveform and an interference signal waveform respectively.

[0077] Further, the dynamic detection module M200 is further configured to execute the following method:

[0078] The predetermined detection constraint includes a temperature constraint, a humidity constraint, and an interference level constraint.

[0079] Further, the dynamic detection module M200 is further configured to execute the following method:

[0080] The partial discharge detector refers to a matching impedance sampler established based on the matching impedance principle, and the interference detector refers to a microstrip coupling sampler established based on a microstrip coupling antenna sensor.

[0081] Furthermore, the dynamic detection module M200 is further configured to execute the following method:

[0082] The expression of the signal detection loss calibration function is as follows: ;

[0083] Wherein, refers to the partial discharge waveform and the effective partial discharge waveform the signal detection loss calibration function between them, refers to the device loss calibration coefficient of the target ultra-wideband, refers to the performance loss calibration coefficient of the partial discharge detector, refers to a predetermined attenuation factor, and .

[0084] Furthermore, the dynamic detection module M200 is further configured to execute the following method:

[0085] Obtain a partial discharge detection specimen;

[0086] Detect the partial discharge detection specimen through the partial discharge detector to obtain a partial discharge waveform under air;

[0087] Place the partial discharge detection specimen in insulating oil, and detect the partial discharge detection specimen through the partial discharge detector to obtain a partial discharge waveform under insulating oil;

[0088] Compare the partial discharge waveform under air with the partial discharge waveform under insulating oil to obtain a waveform deviation;

[0089] Perform weighted calculation on the deviation characteristic parameter set of the waveform deviation after normalization processing to obtain the predetermined attenuation factor .

[0090] Furthermore, the dynamic detection module M200 is further configured to execute the following method:

[0091] The deviation characteristic parameter set at least includes an amplitude deviation parameter and a phase deviation parameter.

[0092] Furthermore, the suppression analysis module M400 is configured to execute the following method:

[0093] Estimate Fourier series coefficients based on the Fourier series method, and use the Fourier series coefficients to obtain an estimated interference waveform;

[0094] According to the interference signal suppression strategy, the interference signal waveform is adjusted with the estimated interference waveform to obtain an effective interference waveform;

[0095] The effective partial discharge waveform and the effective interference waveform are subtracted and canceled to obtain the pure partial discharge waveform.

[0096] Further, the diagnosis and analysis module M500 is used to execute the following method:

[0097] Obtain the historical partial discharge log of the target ultra-wideband;

[0098] Extract the first partial discharge record in the historical partial discharge log, where the first partial discharge record includes a first pure partial discharge waveform and a first partial discharge type;

[0099] Based on the first waveform feature of the first pure partial discharge waveform and the first partial discharge type, a first data set is formed, and supervised learning is performed on the first data set to obtain the partial discharge diagnosis model.

[0100] In summary, any step can be stored as a computer instruction or program in an unrestricted computer memory and can be called and recognized by an unrestricted computer processor, without further limitation here.

[0101] Furthermore, the above technical solutions only reflect the preferred technical solutions of the technical solutions of the embodiments of the present application. Some changes that those skilled in the art may make to some parts thereof all reflect the principles of the novel embodiments of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application.

Claims

1. An anti-interference intelligent detection method for ultra-wideband partial discharge, characterized in that: include: Acquire an anti-interference detection device, wherein the anti-interference detection device includes a partial discharge detector and an interference detector; Based on the synchronization trigger signal, respectively, a partial discharge waveform is obtained by dynamic detection through the partial discharge detector, and an interference signal waveform is obtained by dynamic detection through the interference detector, wherein the partial discharge waveform and the interference signal waveform meet a predetermined synchronization constraint; A signal detection loss calibration function is introduced to calibrate and analyze the partial discharge waveform to obtain an effective partial discharge waveform. The expression of the signal detection loss calibration function is as follows: ； in, Refers to the partial discharge waveform The effective partial discharge waveform The signal detection loss calibration function between is the device loss calibration coefficient for the target ultra-wideband. is the performance loss calibration factor of the PD detector, is a predetermined attenuation factor, and ; Reading an interference signal suppression strategy, and performing a comparative suppression analysis on the effective partial discharge waveform and the interference signal waveform according to the interference signal suppression strategy to obtain a pure partial discharge waveform; The partial discharge diagnosis model is retrieved to perform diagnosis analysis on the pure partial discharge feature set of the pure partial discharge waveform to obtain a partial discharge diagnosis result.

2. The anti-interference intelligent detection method for ultra-wideband partial discharge according to claim 1, characterized in that: Based on the synchronous trigger signal, the partial discharge waveform is obtained by dynamic detection through the partial discharge detector, and the interference signal waveform is obtained by dynamic detection through the interference detector, including: Establishing a fully shielded space, and arranging a predetermined high voltage power supply in the fully shielded space; Under predetermined detection constraints, the target ultra-wide frequency band is pressurized by the predetermined high-voltage power supply, and the target ultra-wide frequency band under pressure is subjected to signal detection by the detector to obtain an initial signal waveform; Wherein, the initial signal waveform includes an initial partial discharge waveform dynamically detected by the partial discharge detector in the detector and an initial interference waveform dynamically detected by the interference detector in the detector; The conditioning of the initial partial discharge waveform and the initial interference waveform based on the signal conditioning strategy is recorded by a digital oscilloscope to obtain a partial discharge waveform and an interference signal waveform respectively.

3. The anti-interference intelligent detection method for ultra-wideband partial discharge according to claim 2, characterized in that: The predetermined detection constraints include temperature constraints, humidity constraints, and interference level constraints.

4. The anti-interference intelligent detection method for ultra-wideband partial discharge as claimed in claim 2, characterized in that: The partial discharge detector refers to a matched impedance sampler established based on the matched impedance principle, and the interference detector refers to a microstrip coupled sampler established based on a microstrip coupled antenna sensor.

5. The anti-interference intelligent detection method for ultra-wideband partial discharge according to claim 1, characterized in that: Also includes: Obtaining partial discharge test samples; The partial discharge detection sample is detected by the partial discharge detector to obtain a partial discharge waveform under air; Placing the partial discharge detection sample in insulating oil, and detecting the partial discharge detection sample by the partial discharge detector to obtain a partial discharge waveform under insulating oil; Comparing the partial discharge waveform under air with the partial discharge waveform under insulating oil to obtain a waveform deviation; The predetermined attenuation factor is obtained by performing weighted calculation on the deviation characteristic parameter set of the normalized waveform deviation. .

6. The anti-interference intelligent detection method for ultra-wideband partial discharge according to claim 5, characterized in that: The deviation characteristic parameter set includes at least an amplitude deviation parameter and a phase deviation parameter.

7. The anti-interference intelligent detection method for ultra-wideband partial discharge according to claim 1, characterized in that: The interference signal suppression strategy is read, and the effective partial discharge waveform and the interference signal waveform are compared and suppressed and analyzed according to the interference signal suppression strategy to obtain a pure partial discharge waveform, including: Estimating Fourier series coefficients based on the Fourier series method, and obtaining an estimated interference waveform using the Fourier series coefficients; According to the interference signal suppression strategy, the interference signal waveform is adjusted with the estimated interference waveform to obtain an effective interference waveform; The effective partial discharge waveform is subtracted and offset from the effective interference waveform to obtain the pure partial discharge waveform.

8. The anti-interference intelligent detection method for ultra-wideband partial discharge as claimed in claim 2, characterized in that: The partial discharge diagnosis model is retrieved to perform diagnosis and analysis on the pure partial discharge feature set of the pure partial discharge waveform to obtain partial discharge diagnosis results, including: Obtaining a historical partial discharge log of the target ultra-wideband; Extracting a first partial discharge record in the historical partial discharge log, wherein the first partial discharge record includes a first pure partial discharge waveform and a first partial discharge type; A first data set is formed based on the first waveform feature of the first pure partial discharge waveform and the first partial discharge type, and supervised learning is performed on the first data set to obtain the partial discharge diagnostic model. 9.Anti-interference intelligent detection system for ultra-wideband partial discharge, characterized in that: The system for implementing the anti-interference intelligent detection method for ultra-wideband partial discharge according to any one of claims 1 to 8 comprises: A detection module, used to obtain an anti-interference detection device, wherein the anti-interference detection device includes a partial discharge detector and an interference detector; A dynamic detection module, for obtaining a partial discharge waveform through dynamic detection by the partial discharge detector and an interference signal waveform through dynamic detection by the interference detector based on a synchronous trigger signal, wherein the partial discharge waveform and the interference signal waveform meet a predetermined synchronization constraint; A calibration and analysis module, used for introducing a signal detection loss calibration function to perform calibration analysis on the partial discharge waveform to obtain an effective partial discharge waveform; A suppression analysis module, used for reading an interference signal suppression strategy, and performing a comparative suppression analysis on the effective partial discharge waveform and the interference signal waveform according to the interference signal suppression strategy to obtain a pure partial discharge waveform; The diagnosis and analysis module is used to call the partial discharge diagnosis model to perform diagnosis and analysis on the pure partial discharge feature set of the pure partial discharge waveform to obtain a partial discharge diagnosis result.

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