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

Abstract

The invention relates to the related technical field of anti-interference detection, in particular to an anti-interference intelligent detection method and system for ultra-wideband partial discharge, and the method comprises the steps: obtaining a partial discharge waveform and an interference signal waveform through a synchronous trigger signal; after signal detection loss calibration, an interference signal suppression strategy is adopted for comparison suppression, a pure partial discharge waveform is obtained, a partial discharge diagnosis model is called, and a diagnosis result is obtained, so that the problems that in ultra-wideband partial discharge detection, the electromagnetic environment is complex, the interference signal frequency range is wide, the interference signal and the partial discharge signal have frequency spectrum overlapping, and the detection accuracy is poor are solved. According to the technical scheme, the technical problem that the requirement for monitoring the state of complex power equipment is difficult to meet is solved, the partial discharge waveform is accurately calibrated, equipment loss and environmental influence are compensated, a detection strategy is optimized in real time according to signal characteristics, efficient separation of interference signals and partial discharge signals and dynamic adjustment in the detection process are achieved, and the detection accuracy is improved. And the purity of the detection signal and the analysis accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field related to anti-interference detection, and in particular 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 insulation defects inside the equipment, thereby giving warnings before a fault occurs and ensuring the safe operation of the equipment. With the continuous expansion of the scale of power systems and the increase in equipment complexity, the requirements for the accuracy and reliability of partial discharge signal detection are also gradually increasing.

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

[0004] In summary, in the prior art, there are technical problems in ultra-wideband partial discharge detection, such as a complex electromagnetic environment, a wide frequency range of interference signals, and spectrum overlap between interference signals and partial discharge signals, which makes it difficult to meet the needs of complex power equipment status monitoring. Summary of the invention

[0005] The present application provides an anti-interference intelligent detection system for ultra-wideband partial discharge, aiming to solve the technical problems in the prior art in which, in ultra-wideband partial discharge detection, the electromagnetic environment is complex and the frequency range of the interference signal is wide, and there is spectrum overlap between the interference signal and the partial discharge signal, making it difficult to meet the needs of complex power equipment status monitoring.

[0006] In view of the above problems, the technical solution to implement this application is: On the one hand, the present application provides an anti-interference intelligent detection method for ultra-wideband partial discharge, wherein the method comprises: obtaining an anti-interference detection device, wherein the anti-interference detection device comprises a partial discharge detector and an interference detector; based on a synchronous trigger signal, dynamically detecting a partial discharge waveform through the partial discharge detector, and dynamically detecting an interference signal waveform through the interference detector, wherein the partial discharge waveform and the interference signal waveform meet a predetermined synchronization constraint; introducing a signal detection loss calibration function to perform calibration analysis on the partial discharge waveform to obtain an effective partial discharge waveform; 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; calling a partial discharge diagnosis model to perform diagnostic analysis on a pure partial discharge feature set of the pure partial discharge waveform to obtain a partial discharge diagnosis result.

[0007] Preferably, based on the synchronous trigger signal, a local discharge waveform is obtained by dynamic detection through the local discharge detector, and an 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 local discharge waveform dynamically detected by the local discharge detector in the detector and an initial interference waveform dynamically detected by the interference detector in the detector; the conditioning of the initial local discharge waveform and the initial interference waveform based on the signal conditioning strategy is recorded by a digital oscilloscope to obtain a local discharge waveform and an interference signal waveform, respectively.

[0008] Preferably, the predetermined detection constraints include temperature constraints, humidity constraints and interference level constraints.

[0009] Preferably, 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.

[0010] Preferably, 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 coefficient of the PD detector, is a predetermined attenuation factor, and .

[0011] Preferably, it also includes: obtaining a partial discharge detection sample; detecting the partial discharge detection sample 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; performing weighted calculation on a deviation characteristic parameter set of the normalized waveform deviation to obtain the predetermined attenuation factor .

[0012] Preferably, the deviation characteristic parameter set includes at least an amplitude deviation parameter and a phase deviation parameter.

[0013] Preferably, 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; 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 from the effective interference waveform to obtain the pure partial discharge waveform.

[0014] Preferably, a partial discharge diagnostic model is called up to perform diagnostic analysis on the pure partial discharge feature set of the pure partial discharge waveform to obtain a partial discharge diagnostic result, 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; forming 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 diagnostic model.

[0015] On the other hand, the present application provides an anti-interference intelligent detection system for ultra-wideband partial discharge, wherein the system includes: a detection module for obtaining 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 of the partial discharge detector and an interference signal waveform through dynamic detection of 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 analysis module 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 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; and a diagnostic analysis module for calling a partial discharge diagnostic model to perform diagnostic analysis on a pure partial discharge feature set of the pure partial discharge waveform to obtain a partial discharge diagnostic result.

[0016] In summary, one or more technical solutions provided in this application, by introducing joint dynamic detection of interference detectors and partial discharge detectors, and time constraints of synchronous trigger signals, accurately calibrate the partial discharge waveform, compensate for equipment losses and environmental influences, and optimize the detection strategy in real time according to signal characteristics, thereby achieving efficient separation of interference signals and partial discharge signals, and dynamically adjusting the detection process to improve the purity of the detection signal and the accuracy of the analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flow chart of an anti-interference intelligent detection method for ultra-wideband partial discharge is provided for this application; Figure 2 A structural schematic diagram of an ultra-wideband partial discharge anti-interference intelligent detection system is provided for this application.

[0018] Explanation of reference numerals: detection module M100, dynamic detection module M200, calibration analysis module M300, suppression analysis module M400, diagnosis analysis module M500. DETAILED DESCRIPTION Embodiment 1

[0019] The present application is described in detail below with reference to the accompanying drawings. Figure 1 As shown, the present application provides an anti-interference intelligent detection method for ultra-wideband partial discharge, wherein the method comprises: S1: Obtain an anti-interference detection device, which 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, wherein the partial discharge waveform and the interference signal waveform meet a predetermined synchronization constraint.

[0020] Specifically, the anti-interference detection equipment is used to detect local 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 local discharge events, and the interference detector is used to identify and measure external interference signals that may affect the local discharge signals. Through the cooperation between the partial discharge detector and the interference detector, the influence of external interference on the detection results can be 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 time or at a predetermined time interval, thereby ensuring the time synchronization between the local discharge waveform and the interference signal waveform.

[0021] Deployment of anti-interference detection equipment includes installation and calibration of partial discharge detectors and interference detectors. Partial discharge detectors are usually placed near high-voltage power equipment so that they can capture weak signals generated by partial discharge events. Interference detectors are used to monitor possible interference sources in the surrounding environment, such as electromagnetic interference, radio waves, etc. Through synchronous trigger signals, partial discharge detectors and interference detectors can collect signals at the same time point or at a predetermined time interval to obtain partial discharge waveforms and interference signal waveforms. In this way, the partial discharge detector and the interference detector cooperate with each other. For example, in the maintenance of high-voltage transformers, the partial discharge detector is installed on the wall of the transformer's oil tank, and the interference detector is installed on the ground around the transformer. By using synchronous trigger signals, when 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 time.

[0022] S3: Introduce a signal detection loss calibration function to perform calibration analysis on the partial discharge waveform to obtain an effective partial discharge waveform; S4: 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; S5: 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.

[0023] 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 partial discharge signal representation; 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, in order 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 the partial discharge accordingly.

[0024] Analyze the captured partial discharge waveform using the signal detection loss calibration function, taking into account the equipment loss calibration factor and the predetermined attenuation factor , adjust the waveform data to compensate for the loss in the signal transmission and detection process, and ensure the accuracy of the partial discharge waveform; according to the read interference signal suppression strategy, compare and analyze the calibrated effective partial discharge waveform and the interference signal waveform, effectively separate the partial discharge signal and the interference signal, improve the accuracy and reliability of partial discharge detection, and provide 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 use these features to diagnose the fault type and severity.

[0025] Specifically, the signal detection loss calibration function includes gain adjustment and filtering of the partial discharge waveform to compensate for the attenuation of cables and sensors; the interference signal suppression strategy includes using a band-stop filter to reduce interference at specific frequencies, or using adaptive filtering technology to dynamically adjust filtering parameters to adapt to changing interference environments; the partial discharge diagnostic model is trained based on empirical data and can identify the association between specific waveform features and fault types, such as discharges in oil-paper insulation that usually manifest as a specific frequency distribution; through these steps, rapid and accurate diagnosis of partial discharge events can be achieved, thereby providing early warning of potential equipment failures and making detection results more reliable.

[0026] Furthermore, 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. The method of the present application includes: A fully shielded space is established, and a predetermined high-voltage power supply is arranged in the fully shielded space; under predetermined detection constraints, a target ultra-wide frequency band is pressurized by the predetermined high-voltage power supply, and a detector is used to perform signal detection on the target ultra-wide frequency band under pressure 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 a signal conditioning strategy is recorded by a digital oscilloscope to obtain a partial discharge waveform and an interference signal waveform, respectively.

[0027] Specifically, the fully shielded space is used to isolate the environment from external electromagnetic interference. It is 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, which is used to apply high voltage to the target ultra-wideband device to simulate the power equipment under actual working conditions, thereby inducing partial discharge phenomena. The predetermined detection constraints refer to a series of conditions that need to be followed when performing partial discharge detection, such as temperature, humidity and interference level, 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 signal quality and reduce noise interference, so as to more accurately analyze and identify the partial discharge waveform and the interference signal waveform.

[0028] A fully shielded space is established. The fully shielded space is made of metal or other electromagnetic shielding materials to isolate external electromagnetic interference. A predetermined high-voltage power supply is arranged inside the fully shielded space to apply high voltage to the target ultra-wideband device. Through the above steps, an interference-free environment is provided for partial discharge detection, ensuring the accuracy and reliability of the detection results.

[0029] In a fully shielded space, high voltage is applied to the target ultra-wideband device through a predetermined high-voltage power supply to simulate actual working conditions. At the same time, a partial discharge detector and an interference detector are used to perform signal detection on the target device under pressure to obtain the initial signal waveform. In the above steps, partial discharge phenomena are induced by simulating actual working conditions, and the partial discharge waveform and interference signal waveform are captured at the same time, providing basic data for subsequent signal analysis.

[0030] Use a digital oscilloscope to perform signal conditioning on the initial partial discharge waveform and the initial interference waveform, such as filtering and amplification, 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 identify and analyze, providing a data basis for subsequent signal separation and diagnosis.

[0031] Furthermore, the present application method comprises: The predetermined detection constraints include temperature constraints, humidity constraints, and interference level constraints.

[0032] Specifically, temperature constraint refers to the control requirement for the environment or equipment temperature when performing partial discharge detection. Temperature changes will affect the characteristics of the partial discharge signal, such as the signal propagation speed and amplitude; humidity constraint is an environmental factor that affects partial discharge detection. The level of humidity can affect the performance of the insulating material and the propagation of the partial discharge signal. Therefore, the environmental humidity needs to be controlled during the detection process; interference level constraint refers to the limitation on the intensity of possible external electromagnetic interference during the partial discharge detection process. To ensure the accuracy of the detection results, the interference level needs to be controlled within a predetermined range to reduce the impact on the detection signal.

[0033] When conducting partial discharge detection, it is necessary to operate under predetermined detection constraints. Specifically, temperature constraints (such as 20℃±2℃) are used to ensure that the temperature of the detection environment or equipment is maintained within a certain range, which involves the use of constant temperature equipment or the selection of testing under specific temperature conditions; humidity constraints (such as 45%±5%) are used to control the humidity of the detection environment, and a dehumidifier or humidifier may be required to adjust the ambient humidity; interference level constraints are used to reduce external electromagnetic interference to below a predetermined level by using shielding equipment, selecting appropriate test time and location, and other measures, thereby ensuring the consistency and controllability of detection conditions, thereby improving the accuracy and reliability of detection results; by controlling environmental factors, the impact of external variables on detection results can be reduced, making detection data more stable and reliable.

[0034] Furthermore, the present application method comprises: 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.

[0035] Specifically, matched impedance means that the load impedance is equal to the source impedance to achieve maximum power transmission. In partial discharge detection, the matched impedance sampler can ensure that the signal transmission efficiency from the detection point to the detection equipment is maximized and reduce signal loss; the microstrip coupled antenna sensor is built based on microstrip line technology. The 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 uses 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.

[0036] The partial discharge detector refers to a matching impedance sampler established based on the matching impedance principle, which ensures that the signal loss is minimized during the signal transmission 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, and the interference signals captured by the microstrip coupling antenna sensor are coupled and transmitted through the microstrip coupling sampler for further analysis and processing. Preferably, the partial discharge detector improves the transmission efficiency of the signal and reduces the signal loss through the matching impedance principle, thereby improving the detection accuracy of the partial discharge signal. The interference detector can effectively capture and measure the interference signal through the microstrip coupling technology, which provides a basis for subsequent signal processing and analysis.

[0037] Furthermore, the present application method comprises: 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 coefficient of the PD detector, is a predetermined attenuation factor, and .

[0038] Specifically, the signal detection loss calibration function is: ,in, It refers to the device loss calibration coefficient of the target ultra-wideband, which reflects the signal loss of the device itself. It 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, reflects the loss of the signal by the detector, and describes the degree of signal attenuation with frequency; It refers to the predetermined attenuation factor, which describes the degree of signal attenuation with frequency. During signal transmission, high-frequency signals usually decay faster than low-frequency signals. The predetermined attenuation factor Used to correct for this frequency-dependent attenuation.

[0039] In the calibration analysis of 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 restored more accurately, providing a high-quality data basis for subsequent signal analysis and fault diagnosis.

[0040] Furthermore, the present application method also includes: Acquire a partial discharge detection sample; detect the partial discharge detection sample by the partial discharge detector to obtain a partial discharge waveform under air; place the partial discharge detection sample in insulating oil, and detect the partial discharge detection sample by 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 a deviation characteristic parameter set of the normalized waveform deviation to obtain the predetermined attenuation factor .

[0041] Specifically, partial discharge test specimen refers to a sample used for partial discharge detection, which can be a part of power equipment, such as cables, insulating materials, etc., and is used to simulate partial discharge phenomena under actual working conditions under predetermined detection constraints; partial discharge waveform under air refers to the waveform data obtained when the partial discharge test specimen is subjected to partial discharge detection in air, reflecting the partial discharge characteristics without the influence of other media; partial discharge waveform under insulating oil refers to the waveform data obtained when the partial discharge test specimen is placed in insulating oil for partial discharge detection. Insulating oil is a commonly used liquid insulating material with different properties from air, which will affect the propagation of partial discharge signals; waveform deviation refers to the difference between the partial discharge waveform under air and the partial discharge waveform under insulating oil. The waveform deviation provides information about the changes in the discharge characteristics of the partial discharge test specimen in different media; the deviation characteristic parameter set refers to the set of key parameters extracted from the waveform deviation, such as amplitude deviation, phase deviation, etc., which can characterize the differences between the waveforms.

[0042] Obtain or prepare samples for partial discharge detection, which should be able to represent the insulating materials or structures in actual power equipment; place the partial discharge detection sample in the air, use the partial discharge detector to detect it, and record the waveform data generated by the partial discharge event; place the partial discharge detection sample in insulating oil, use the partial discharge detector to detect it again, and record the waveform data of the partial discharge event in the insulating oil. Further, compare the partial discharge waveforms under air and insulating oil, analyze the difference between the two, and obtain the waveform deviation; extract key deviation characteristic parameters from the waveform deviation, such as amplitude deviation and phase deviation; normalize the extracted deviation characteristic parameter set, and obtain the predetermined attenuation factor through weighted calculation. , used to calibrate the partial discharge detection signal of the actual cable in operation to compensate for the signal attenuation caused by the change of the medium, thereby improving the accuracy and reliability of the detection. In the above steps, by comparing the differences in partial discharge waveforms under different media, the performance changes of the partial discharge detection samples under actual working conditions are evaluated, and the partial discharge behavior of actual power equipment in different environments is more accurately simulated and predicted.

[0043] Furthermore, the present application method comprises: The deviation characteristic parameter set includes at least an amplitude deviation parameter and a phase deviation parameter.

[0044] Specifically, the amplitude deviation parameter is a parameter that describes the amplitude change of the local discharge waveform in different media (such as air and insulating oil), reflecting the change in the intensity of the local discharge signal; the phase deviation parameter is a parameter used for the phase change of the local discharge waveform in different media, reflecting the time delay or advance of the local discharge signal in the propagation process, and is used to analyze the signal propagation characteristics and medium influence.

[0045] When comparing the partial discharge waveform under air and the partial discharge waveform under insulating oil, the amplitude difference between the two waveforms is measured and recorded to reflect the propagation characteristics and attenuation of the partial discharge signal in different media. Similarly, when comparing the two waveforms, the phase difference between the two waveforms is measured and recorded to reveal the propagation speed and path changes of the partial discharge signal in different media. The extracted amplitude deviation parameters and phase deviation parameters are combined 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 calculations, the predetermined attenuation factor is obtained. , used to calibrate the partial discharge detection signal of the actual cable in different media, and improve 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 is provided for signal calibration and fault diagnosis; the deviation parameters of amplitude and phase are used to evaluate the partial discharge characteristics and the influence of the medium, which helps to understand and predict the partial discharge behavior more accurately.

[0046] Further, 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. The method of the present application includes: Based on the Fourier series method, Fourier series coefficients are estimated, and the Fourier series coefficients are used to obtain an estimated interference waveform; 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.

[0047] Specifically, the Fourier series method is used to represent a periodic function as the 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 amplitude and phase of each sine and cosine term, so that the original signal can be reconstructed; the estimated interference waveform is the interference signal waveform reconstructed based on the Fourier series coefficients, which 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, thereby separating the desired signal.

[0048] 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; according to the pre-set interference signal suppression strategy, make adjustments based on the estimated interference waveform to obtain an effective interference waveform that is closer to the actual interference signal; subtract the effective partial discharge waveform from the effective interference waveform to offset the influence of the interference signal and obtain a pure partial discharge waveform. In the above steps, through precise signal processing technology, a pure partial discharge signal is separated from the mixed signal, the interference waveform is estimated and adjusted, the influence of the interference signal on the partial discharge signal is effectively reduced, and the partial discharge of the transformer is accurately analyzed and diagnosed, thereby improving the accuracy and reliability of partial discharge detection.

[0049] Furthermore, the partial discharge diagnosis model is retrieved 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 the present application includes: Acquire a historical partial discharge log of the target ultra-wideband; extract 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; form a first data set based on a 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 diagnostic model.

[0050] Specifically, the historical partial discharge log refers to a log file that records partial discharge events that occurred in a specific device or system in the past, containing detailed information on each partial discharge event, such as time, location, waveform data and type; the first partial discharge record is a record of a single partial discharge event extracted from the historical partial discharge log, including the pure partial discharge waveform and partial discharge type of the event; the first waveform features refer to the key features extracted from the first pure partial discharge waveform, which can characterize the characteristics of partial discharge events, such as the amplitude, frequency, duration, etc. of the waveform.

[0051] Supervised learning is learning from labeled training data. Each training sample contains input data and corresponding output labels. Specifically, supervised learning is used to train the model to identify the relationship between specific partial discharge waveform features and partial discharge types; obtain the historical partial discharge log of the target ultra-wideband device, which records all partial discharge events that have occurred in the past; extract the first partial discharge record from the historical partial discharge log, which includes the pure partial discharge waveform of the event and the known partial discharge type; construct a first data set 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), and the first data set is used to train the partial discharge diagnosis model; supervised learning is performed on the partial discharge diagnosis model using the constructed first data set, and how to identify and classify different partial discharge events is learned by analyzing the relationship between waveform features and partial discharge types. The partial discharge diagnosis model is constructed through supervised learning. The partial discharge diagnosis model learns the association between the characteristics of the partial discharge waveform and the partial discharge type from historical data, so that when a new partial discharge event occurs, its waveform features are analyzed and the partial discharge type is predicted, providing fast and accurate diagnosis.

[0052] In summary, the beneficial effects of the embodiments of the present application are: Due to the adoption of anti-interference detection equipment, the anti-interference detection equipment includes a partial discharge detector and an interference detector; 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, wherein the partial discharge waveform and the interference signal waveform meet the predetermined synchronization constraint; the signal detection loss calibration function is introduced to calibrate and analyze the partial discharge waveform to obtain an effective partial discharge waveform; the interference signal suppression strategy is read, and the effective partial discharge waveform and the interference signal waveform are compared and suppressed according to the interference signal suppression strategy to obtain a pure partial discharge waveform; the partial discharge diagnosis model is called to diagnose and analyze the pure partial discharge feature set of the pure partial discharge waveform to obtain the partial discharge diagnosis result. This application provides an anti-interference intelligent detection method for ultra-wideband partial discharge, accurately calibrates the partial discharge waveform, compensates for equipment loss and environmental impact, optimizes the detection strategy in real time according to the signal characteristics, realizes the efficient separation of interference signals and partial discharge signals, and dynamically adjusts the detection process to improve the purity of the detection signal and the technical effect of analysis accuracy. Embodiment 2

[0053] Based on the same inventive concept as the anti-interference intelligent detection method for ultra-wideband partial discharge in the aforementioned embodiment, Figure 2 As shown, the embodiment of the present application provides an anti-interference intelligent detection system for ultra-wideband partial discharge, wherein the system includes: A detection module M100, 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 M200, 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 analysis module M300, 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; The suppression analysis module M400 is used to read the interference signal suppression strategy, and perform 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 M500 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.

[0054] Furthermore, the dynamic detection module M200 is used to perform the following method: 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.

[0055] Furthermore, the dynamic detection module M200 is also used to perform the following method: The predetermined detection constraints include temperature constraints, humidity constraints, and interference level constraints.

[0056] Furthermore, the dynamic detection module M200 is also used to perform the following method: 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.

[0057] Furthermore, the dynamic detection module M200 is also used to perform the following method: 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 coefficient of the PD detector, is a predetermined attenuation factor, and .

[0058] Furthermore, the dynamic detection module M200 is also used to perform the following method: 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. .

[0059] Furthermore, the dynamic detection module M200 is also used to perform the following method: The deviation characteristic parameter set includes at least an amplitude deviation parameter and a phase deviation parameter.

[0060] Furthermore, the inhibition analysis module M400 is used to perform the following method: 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.

[0061] Furthermore, the diagnostic analysis module M500 is used to perform the following method: 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.

[0062] In summary, any step can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor, and no unnecessary restrictions are made here.

[0063] Furthermore, the above-mentioned technical scheme only reflects the preferred technical scheme of the technical scheme of the embodiment of the present application. Some changes that may be made to some parts thereof by technicians in this technical field all reflect the novel principles of the embodiment of the present application. Obviously, technicians in this field 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; 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 as claimed in claim 4, characterized in that: 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 coefficient of the PD detector, is a predetermined attenuation factor, and .

6. The anti-interference intelligent detection method for ultra-wideband partial discharge according to claim 5, 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. .

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

8. 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.

9. The anti-interference intelligent detection method for ultra-wideband partial discharge according to 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. 10.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 9 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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