A high-voltage electrical equipment inspection method and system based on microphone array measurement

Abstract

The present application relates to the technical field of power equipment inspection, and in particular to a method and system for inspecting high-voltage electrical equipment based on microphone array measurement. The method comprises: obtaining array acoustic signal data, analyzing the array acoustic signal data, and determining acoustic signal characteristic information; obtaining a layered structure parameter set and an insulating medium parameter set of the target electrical equipment, and performing targeted compensation and correction on the acoustic signal characteristic information according to the layered structure parameter set and the insulating medium parameter set, and determining abnormal voiceprint characteristic information; generating abnormal component information according to the abnormal voiceprint characteristic information, and determining and outputting an abnormal detection report. The present application realizes non-contact real-time detection of high-voltage electrical equipment in operation, thereby enhancing the adaptability of the detection process to high-voltage electrical equipment with a multi-layer composite structure and filled with insulating medium, and improving the accuracy of locating the fault position inside the equipment.

Description

Technical Field

[0001] The present application relates to the technical field of power equipment inspection, and in particular to a high-voltage electrical equipment inspection method and system based on microphone array measurement. Background Art

[0002] Acoustic imaging technology uses the propagation characteristics of sound waves, combined with signal processing technology, to generate images of the sound field distribution inside or on the surface of an object. By capturing the reflection, scattering, transmission or radiation characteristics of sound waves, it converts acoustic information into visual images and is widely used in industrial inspection processes.

[0003] However, existing acoustic imaging technology has difficulty in accurately locating the internal fault location of high-voltage electrical equipment with multi-layer complex structures and dielectric isolation characteristics when performing anomaly detection, resulting in difficulty in ensuring the accuracy and reference value of the detection results. Summary of the Invention

[0004] The present application provides a high-voltage electrical equipment inspection method and system based on microphone array measurement to solve the above technical problems.

[0005] In a first aspect, the present application provides a high-voltage electrical equipment inspection method based on microphone array measurement, the method comprising:

[0006] Acquiring array acoustic signal data of a target electrical device, analyzing the array acoustic signal data, and determining acoustic signal characteristic information;

[0007] The acoustic signal feature information is a feature set extracted from the array acoustic signal data and can be used to characterize the operating state of the target device;

[0008] Obtaining a layered structure parameter set and an insulating medium parameter set of the target electrical device, and performing targeted compensation and correction on the acoustic signal characteristic information based on the layered structure parameter set and the insulating medium parameter set to determine abnormal voiceprint characteristic information;

[0009] The abnormal voiceprint feature information is sound feature information used to map the local abnormal discharge situation inside the target electrical equipment;

[0010] Based on the abnormal voiceprint feature information, abnormal component information is generated, and an abnormal detection report is determined and output.

[0011] Through this solution, based on acoustic imaging technology, according to the characteristics of abnormal sound signals generated when high-voltage electrical equipment has partial discharge, by analyzing the array acoustic signal data, the acoustic signal feature information used to characterize the current operating status of the high-voltage electrical equipment is extracted from the array acoustic signal data. This is used as the data basis for judging whether the high-voltage electrical equipment has partial discharge anomalies, and non-contact real-time detection of the high-voltage electrical equipment in operation is realized. On this basis, the influence of the internal layered structure and insulating medium of the target electrical equipment on the sound signal is used as the basis for correcting the acoustic signal feature information. The acoustic signal feature information is targetedly compensated and corrected to obtain abnormal soundprint feature information that can accurately characterize the actual partial discharge situation inside the electrical equipment. The adaptability of the detection process to high-voltage electrical equipment with a multi-layer composite structure and filled with insulating medium is enhanced, and the accuracy of locating the fault position inside the equipment is improved. Based on the abnormal soundprint feature information, abnormal component information is generated, and the corresponding visual abnormality detection report is provided to the corresponding maintenance personnel, thereby improving the reference value of the detection results.

[0012] Optionally, the array acoustic signal data is obtained through a ring microphone array;

[0013] The number of microphones in the annular microphone array is not less than 128;

[0014] The acoustic measurement frequency range of the annular microphone array is 2 kHz to 40 kHz.

[0015] Through this solution, the microphone array mode, number of microphones and acoustic measurement frequency range are constrained to meet the sound source localization needs under the complex three-dimensional structure of high-voltage electrical equipment, improve the sound source localization accuracy, suppress environmental noise, and improve the signal-to-noise ratio, thereby improving the comprehensiveness and accuracy of the detection process.

[0016] Optionally, analyzing the array acoustic signal data to determine acoustic signal feature information includes:

[0017] Extracting continuous frame features of the array acoustic signal data according to a preset unit sound frame time;

[0018] According to the continuous frame features, the array acoustic signal data is framed to extract the acoustic signal time domain features, acoustic signal frequency domain features and time-frequency joint non-stationary features;

[0019] Based on the acoustic signal time domain features, the acoustic signal frequency domain features and the time-frequency joint non-stationary features, and according to the mechanical vibration acoustic features and the partial discharge acoustic features, the mechanical vibration acoustic signal and the partial discharge acoustic signal in the array acoustic signal data are separated;

[0020] constructing the acoustic signal characteristic information according to the partial discharge acoustic signal;

[0021] The mechanical vibration acoustic characteristics are characterized by being dominated by low-frequency harmonic groups and exhibiting periodic attenuation characteristics;

[0022] The local discharge acoustic characteristics are manifested as high-frequency pulse clusters and have random burst characteristics.

[0023] Through this solution, the array acoustic signal data is framed and processed, and the time domain features, frequency domain features and time-frequency joint non-stationary features of the acoustic signal are extracted respectively. On this basis, the mechanical vibration acoustic signal and the partial discharge acoustic signal in the array acoustic signal data are separated according to the mechanical vibration acoustic characteristics and the partial discharge acoustic characteristics. Based on the partial discharge acoustic signal, the acoustic signal feature information is constructed so that the acoustic signal feature information points to the abnormal discharge situation inside the equipment, avoiding the confusion between the vibration caused by the operation of the equipment itself and the partial discharge anomaly, and preventing invalid maintenance or delayed repairs due to misjudgment.

[0024] Optionally, the layered structure parameter set includes structure layer thickness distribution information, structure material information and geometric topology information;

[0025] The insulating medium parameter set includes medium type, medium dynamic viscosity coefficient, medium sound velocity propagation characteristics and medium pressure reference.

[0026] Through this scheme, a layered structure parameter set is constructed based on the structural layer thickness distribution information, structural material information and geometric topology information. The influence of the multi-layer structure inside high-voltage electrical equipment on the partial discharge acoustic signal is reflected from the three dimensions of material properties, material thickness and geometric shape. At the same time, an insulating medium parameter set is constructed based on the medium type, medium dynamic viscosity coefficient, medium sound speed propagation characteristics and medium pressure benchmark, providing a reliable data basis for a comprehensive analysis of the influence of insulating media on acoustic signals.

[0027] Optionally, performing targeted compensation and correction on the acoustic signal characteristic information according to the layered structure parameter set and the insulating medium parameter set to determine abnormal voiceprint characteristic information includes:

[0028] Constructing a physical field simulation model of sound propagation based on multi-layer geometric structures according to the layered structure parameter set;

[0029] determining the reflection-transmission attenuation coefficient of the partial discharge acoustic signal in different layered structures according to the physical field simulation model;

[0030] performing phase compensation correction on the propagation path of the partial discharge acoustic signal according to the insulating medium parameter set to determine the dielectric absorption coefficient;

[0031] According to the reflection-transmission attenuation coefficient and the medium absorption coefficient, targeted compensation and correction are performed on the partial discharge acoustic signal to determine the abnormal voiceprint feature information.

[0032] Through this scheme, a physical field simulation model is constructed based on the layered structure parameter set to simulate the negative impact of the acoustic signal during the propagation process between different layered structures inside the high-voltage electrical equipment, and the corresponding reflection-transmission attenuation coefficient is fitted. Based on the insulating medium parameter set, the propagation characteristics of the acoustic signal in the insulating medium are analyzed, and the dielectric absorption coefficient reflecting the influence of the insulating medium on the propagation of the acoustic signal is fitted. The attenuation characteristics of the acoustic signal under the dual influence are characterized by the reflection-transmission attenuation coefficient and the dielectric absorption coefficient, so as to reversely deduce the actual sound signal characteristics caused by partial discharge, accurately locate the abnormal soundprint feature information, and improve the accuracy of the judgment of local abnormal discharge.

[0033] Optionally, constructing a physical field simulation model based on multi-layer geometric structure sound propagation according to the layered structure parameter set includes:

[0034] Constructing a three-dimensional spatial grid model based on the thickness distribution information of the structural layer and the geometric topology information, parametrically characterizing the geometric features of each layer of the structure, and determining a plurality of hierarchical grid parameter nodes;

[0035] Based on the structural material information, the acoustic impedance parameters of the corresponding structural material are loaded at each of the hierarchical grid parameter nodes. According to the acoustic impedance parameters, the time delay characteristics, attenuation characteristics, and superposition characteristics of the partial discharge acoustic signal in each propagation path are simulated and marked by a ray tracing algorithm to construct the physical field simulation model.

[0036] Through this scheme, a three-dimensional spatial grid model containing hierarchical grid parameter nodes is constructed according to the structural layer thickness distribution information and geometric topology information, so as to realize the sound field simulation of the three-dimensional irregular structure inside the high-voltage electrical equipment and eliminate the sound source positioning offset caused by the two-dimensional model. On this basis, based on the acoustic impedance parameters reflected in the structural material information, the time delay characteristics, attenuation characteristics and superposition characteristics of the partial discharge acoustic signal in each propagation path are simulated and marked through the ray tracing algorithm, and a physical field simulation model is constructed. The high-precision simulation of the sound wave propagation characteristics under the complex structure of the high-voltage equipment is realized, which provides a reliable numerical basis for the physical field compensation of abnormal soundprint characteristics and significantly improves the positioning accuracy and diagnostic reliability of partial discharge detection.

[0037] Optionally, performing phase compensation correction on the propagation path of the partial discharge acoustic signal according to the insulating medium parameter set to determine the dielectric absorption coefficient includes:

[0038] Constructing a basic dynamic propagation velocity field model of the partial discharge acoustic signal in the insulating medium according to the medium type and the sound velocity propagation characteristics of the medium;

[0039] Based on the basic dynamic propagation velocity field model, according to the medium dynamic viscosity coefficient and the medium pressure reference, simulating the viscous phase delay of the partial discharge acoustic signal in the insulating medium;

[0040] The viscous phase delay is positively correlated with the dynamic viscosity coefficient of the medium;

[0041] The viscous phase delay is negatively correlated with the medium pressure reference;

[0042] The viscous phase delay is normalized to determine the medium absorption coefficient.

[0043] Through this solution, a basic dynamic propagation velocity field model is constructed based on the medium type and the sound speed propagation characteristics of the medium to reflect the basic propagation characteristics of the sound signal in the current insulating medium. On this basis, the dynamic viscosity coefficient of the medium and the medium pressure reference are introduced to simulate the viscous phase delay of the partial discharge sound signal under the dual influence of the viscosity and pressure of the insulating medium. The viscous phase delay is normalized to obtain the medium absorption coefficient to accurately reflect the actual propagation state of the sound signal in the insulating medium and improve the accuracy of subsequent positioning analysis of the partial discharge position.

[0044] Optionally, generating abnormal component information according to the abnormal voiceprint feature information includes:

[0045] After determining several levels of grid parameter nodes in the physical field simulation model, substituting the reflection-transmission attenuation coefficient and the medium absorption coefficient into an inverse ray tracing algorithm, inverting the sound source propagation path, determining the coordinate point of the sound source of the partial discharge sound signal in the three-dimensional space grid model, and generating the three-dimensional coordinates of the abnormal position;

[0046] Based on the geometric topology information and the three-dimensional coordinates of the abnormal position, determining the relative position of the abnormal equipment component and the partial discharge;

[0047] According to the relative position of the abnormal equipment component and the partial discharge, a preset equipment abnormality information database is retrieved to determine abnormality troubleshooting suggestions;

[0048] The abnormal component information is constructed based on the abnormal equipment component, the relative position of the partial discharge and the abnormality troubleshooting suggestion.

[0049] Through this solution, based on the physical field simulation model, according to the reflection-transmission attenuation coefficient and the dielectric absorption coefficient, the inverse ray tracing algorithm is used to deduce the propagation path of the currently collected partial discharge acoustic signal, and then locate the sound source of the partial discharge acoustic signal inside the high-voltage electrical equipment, and obtain the three-dimensional coordinates of the abnormal position. Combined with the geometric topology information, the relative position of the abnormal equipment component and the partial discharge is determined. In this way, the preset equipment abnormality information database is retrieved, and abnormality troubleshooting suggestions are determined. According to the abnormal equipment components, the relative position of the partial discharge and the abnormality troubleshooting suggestions, the abnormal component information is constructed to achieve accurate positioning of the abnormal discharge position inside the high-voltage electrical equipment, and provide corresponding abnormality troubleshooting suggestions, effectively improving the inspection and maintenance efficiency and effectiveness of subsequent maintenance personnel.

[0050] Optionally, the method further includes:

[0051] Obtain maintenance personnel's maintenance feedback information, analyze the maintenance personnel's maintenance feedback information, and determine whether the maintenance personnel adopt the abnormality troubleshooting suggestions;

[0052] If the maintenance personnel adopt the corresponding abnormality troubleshooting suggestion, then the impact factor of the abnormality troubleshooting suggestion is increased;

[0053] If the maintenance personnel does not adopt the corresponding abnormality troubleshooting suggestion, the troubleshooting process in the maintenance personnel's maintenance feedback information is included in the troubleshooting suggestion list corresponding to the relative position of the partial discharge under the abnormal equipment component in the preset equipment abnormality information database, and the corresponding impact factor is set as a preset impact baseline value;

[0054] The abnormality troubleshooting suggestions in the troubleshooting suggestion list are sorted according to the numerical values ​​of their corresponding impact factors.

[0055] Through this solution, based on the maintenance personnel's feedback information collected and utilizing the adjustment mechanism of influencing factors, the abnormality troubleshooting suggestions in the abnormality troubleshooting suggestion list are dynamically updated and the recommendation priority is adjusted. A complete closed loop of "suggestion generation-field verification-knowledge evolution" is established, which enables the abnormality troubleshooting system to have the ability to continuously self-optimize to adapt to complex actual situations and further improve the maintenance efficiency and maintenance results of maintenance personnel.

[0056] In a second aspect, the present application provides a high-voltage electrical equipment inspection system based on microphone array measurement, the system comprising:

[0057] A feature analysis module, configured to acquire array acoustic signal data, analyze the array acoustic signal data, and determine acoustic signal feature information;

[0058] a feature correction module, configured to obtain a layered structure parameter set and an insulating medium parameter set of the target electrical device, and to perform targeted compensation and correction on the acoustic signal feature information based on the layered structure parameter set and the insulating medium parameter set to determine abnormal voiceprint feature information;

[0059] The abnormality positioning module is used to generate abnormal component information based on the abnormal voiceprint feature information, and determine and output an abnormality detection report. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0061] Figure 1 A schematic diagram of an application scenario provided in one embodiment of the present application;

[0062] Figure 2 A flowchart of a high-voltage electrical equipment inspection method based on microphone array measurement provided in one embodiment of the present application;

[0063] Figure 3 A schematic structural diagram of a high-voltage electrical equipment inspection system based on microphone array measurement is provided in one embodiment of the present application. DETAILED DESCRIPTION

[0064] To make the purpose, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0065] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0066] The embodiments of the present application are described in further detail below with reference to the accompanying drawings.

[0067] However, existing acoustic imaging technology has difficulty in accurately locating the internal fault location of high-voltage electrical equipment with multi-layer complex structures and dielectric isolation characteristics when performing anomaly detection, resulting in difficulty in ensuring the accuracy and reference value of the detection results.

[0068] Based on this, the present application provides a high-voltage electrical equipment inspection method and system based on microphone array measurement. Based on acoustic imaging technology, according to the characteristics of abnormal sound signals generated when high-voltage electrical equipment is partially discharged, by analyzing the array sound signal data, the sound signal feature information used to characterize the current operating state of the high-voltage electrical equipment is extracted from the array sound signal data, which is used as the data basis for judging whether the high-voltage electrical equipment has partial discharge abnormalities, thereby realizing non-contact real-time detection of the high-voltage electrical equipment in operation. On this basis, the influence of the internal layered structure and insulating medium of the target electrical equipment on the sound signal is used as the basis for correcting the sound signal feature information, and the sound signal feature information is targetedly compensated and corrected to obtain abnormal soundprint feature information that can accurately characterize the actual partial discharge situation inside the electrical equipment. This enhances the adaptability of the detection process to high-voltage electrical equipment with a multi-layer composite structure and filled with insulating medium, improves the accuracy of locating the fault position inside the equipment, generates abnormal component information based on the abnormal soundprint feature information, and provides the corresponding visual abnormality detection report to the corresponding maintenance personnel, thereby improving the reference value of the detection results.

[0069] Figure 1 This is a schematic diagram of an application scenario provided by this application. In the process of detecting abnormal partial discharge of high-voltage electrical equipment, the method provided by this application is applied to improve the accuracy of abnormal partial discharge detection of high-voltage electrical equipment with multi-layer complex structures and dielectric isolation characteristics.

[0070] Specifically, the method of the present application is applied to any server that communicates with a microphone array and obtains array acoustic signal data provided by the microphone array through the server. Based on acoustic imaging technology, according to the characteristics of abnormal acoustic signals generated when local discharge occurs in high-voltage electrical equipment, the array acoustic signal data is analyzed to extract acoustic signal feature information from the array acoustic signal data used to characterize the current operating state of the high-voltage electrical equipment. This is used as the data basis for determining whether there is a local discharge abnormality in the high-voltage electrical equipment, thereby achieving non-contact real-time detection of the operating high-voltage electrical equipment. On this basis, the influence of the internal layered structure and insulating medium of the target electrical equipment on the acoustic signal is used as the basis for correcting the acoustic signal feature information. The acoustic signal feature information is targetedly compensated and corrected to obtain abnormal acoustic signature information that can accurately characterize the actual local discharge situation inside the electrical equipment. This enhances the adaptability of the detection process to high-voltage electrical equipment with a multi-layer composite structure and filled with insulating medium, improves the accuracy of locating the fault location inside the equipment, generates abnormal component information based on the abnormal acoustic signature information, and provides a corresponding visual abnormality detection report to the corresponding maintenance personnel, thereby improving the reference value of the detection results.

[0071] For specific implementation methods, please refer to the following embodiments.

[0072] Figure 2 This is a flow chart of a high-voltage electrical equipment inspection method based on microphone array measurement provided in one embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes:

[0073] S201: Acquire array acoustic signal data, analyze the array acoustic signal data, and determine acoustic signal feature information.

[0074] The array acoustic signal data may be a set of acoustic signal data generated during the operation of the target high-voltage electrical equipment and collected by a microphone array.

[0075] The acoustic signal feature information may be a feature set extracted from array acoustic signal data and can be used to characterize the operating status of the device.

[0076] Specifically, high-voltage electrical equipment is a key equipment node in the power transmission process. The detection and maintenance of periodic partial discharge anomalies of high-voltage electrical equipment are the basis for maintaining a continuous and good power supply. However, due to the presence of high-voltage current during the operation of high-voltage electrical equipment, the detection of high-voltage electrical equipment in operation is highly dangerous, and power outage detection will directly affect the continuity of power supply. Based on acoustic imaging technology, according to the characteristics of abnormal sound signals generated when high-voltage electrical equipment partially discharges, the sound signals of high-voltage electrical equipment in operation are collected through a microphone array to obtain array sound signal data. By analyzing the array sound signal data, the sound signal feature information in the array sound signal data used to characterize the current operating status of the high-voltage electrical equipment is extracted, which is used as the data basis for further judging whether there is partial discharge anomaly in the high-voltage electrical equipment, thereby realizing non-contact real-time detection of high-voltage electrical equipment in operation.

[0077] S202: Obtain a layered structure parameter set and an insulating medium parameter set of the target electrical equipment, perform targeted compensation and correction on the acoustic signal characteristic information based on the layered structure parameter set and the insulating medium parameter set, and determine abnormal voiceprint characteristic information.

[0078] The target electrical device may be a high-voltage electrical device currently being inspected.

[0079] The layered structure parameter set may be a parameter set used to characterize the internal layered device structure characteristics of the high-voltage electrical equipment, and the layered structure parameter set may be provided by the equipment designer.

[0080] The insulating medium parameter set may be a parameter set used to characterize the characteristics of the insulating medium filled inside the high-voltage electrical equipment, and the insulating medium parameter set may be provided by the equipment designer.

[0081] The abnormal voiceprint feature information may be sound feature information used to map the local abnormal discharge situation inside the high-voltage electrical equipment.

[0082] Specifically, when existing acoustic imaging technology performs local abnormal discharge detection on high-voltage electrical equipment (such as transformers, enclosed gas-insulated switches, etc.) with a multi-layer composite structure and filled with insulating media, the collected sound signals are affected by both the attenuation caused by the multi-layer composite structure inside the equipment and the distortion caused by the insulating medium, resulting in large fluctuations in the accuracy of the detection results. It is difficult to accurately locate the specific abnormal discharge location inside the equipment, and it is impossible to provide equipment maintenance personnel with detection results with high reference value. This scheme collects the internal structure parameter set and insulating medium parameter set of the target electrical equipment, and uses the influence of the internal layered structure and insulating medium of the target electrical equipment on the sound signal as the basis for correcting the characteristic information of the sound signal. Targeted compensation and correction are performed on the characteristic information of the sound signal to obtain abnormal soundprint characteristic information that can accurately characterize the actual local discharge situation inside the electrical equipment.

[0083] S203. Generate abnormal component information based on abnormal voiceprint feature information, and determine and output an abnormal detection report.

[0084] The abnormal component information may include the location of the faulty equipment component, the relative location of the partial discharge, and abnormality troubleshooting suggestions, which are of high reference value to equipment maintenance personnel.

[0085] The anomaly detection report may be a visual report document corresponding to the abnormal component information.

[0086] Specifically, traditional detection methods only output simple alarm signals and lack precise positioning and maintenance guidance of faulty components, resulting in low maintenance efficiency. This step uses reverse sound source tracking and equipment topology mapping technology to map and analyze abnormal soundprint feature information, and generates abnormal component information containing the location of faulty equipment components, the relative position of partial discharges, and abnormal troubleshooting suggestions, which are of high reference value to equipment maintenance personnel. The abnormal component information is visualized through data visualization technology to generate corresponding abnormal detection reports. The abnormal detection reports are provided to the corresponding equipment maintenance personnel for reference by using human-computer interaction equipment components, such as high-definition display screens.

[0087] Through this solution, based on acoustic imaging technology, according to the characteristics of abnormal sound signals generated when high-voltage electrical equipment has partial discharge, by analyzing the array acoustic signal data, the acoustic signal feature information used to characterize the current operating status of the high-voltage electrical equipment is extracted from the array acoustic signal data. This is used as the data basis for judging whether the high-voltage electrical equipment has partial discharge anomalies, and non-contact real-time detection of the high-voltage electrical equipment in operation is realized. On this basis, the influence of the internal layered structure and insulating medium of the target electrical equipment on the sound signal is used as the basis for correcting the acoustic signal feature information. The acoustic signal feature information is targetedly compensated and corrected to obtain abnormal soundprint feature information that can accurately characterize the actual partial discharge situation inside the electrical equipment. The adaptability of the detection process to high-voltage electrical equipment with a multi-layer composite structure and filled with insulating medium is enhanced, and the accuracy of locating the fault position inside the equipment is improved. Based on the abnormal soundprint feature information, abnormal component information is generated, and the corresponding visual abnormality detection report is provided to the corresponding maintenance personnel, thereby improving the reference value of the detection results.

[0088] In some embodiments, the array acoustic signal data is obtained through a circular microphone array; the number of microphones in the circular microphone array is no less than 128; and the acoustic measurement frequency range of the circular microphone array is 2 kHz-40 kHz.

[0089] The annular microphone array may be an array structure composed of multiple microphones arranged in a circular geometry.

[0090] The acoustic measurement frequency range may be a frequency interval within which the ambient microphone array can effectively detect, analyze, and generate an acoustic image.

[0091] Specifically, the traditional linear microphone array in traditional acoustic imaging technology has the problem of directionality sensitivity, which makes it difficult to adapt to the sound source positioning needs under the complex three-dimensional structure of high-voltage electrical equipment. The circular array can eliminate the amplitude-frequency response differences caused by the incident angle of the sound wave by evenly distributing microphones 360°, ensuring that sound signals from any direction can be received symmetrically, and the circular array structure can generate a three-dimensional sound field directivity diagram through a beamforming algorithm, significantly improving the accuracy of sound source positioning; according to the spatial sampling theorem, the sound source positioning accuracy is positively correlated with the microphone density. Setting the number of microphones in the circular microphone array to no less than 128 can achieve sub-centimeter sound source positioning accuracy, and high-density microphones can suppress environmental noise through spatial filtering, greatly improving the signal-to-noise ratio; setting the acoustic measurement frequency range of the circular microphone array to 2kHz-40kHz can effectively cover the sound signals reflected by different types of local abnormal discharges, thereby improving the comprehensiveness of the detection process.

[0092] Through this solution, the microphone array mode, number of microphones and acoustic measurement frequency range are constrained to meet the sound source localization needs under the complex three-dimensional structure of high-voltage electrical equipment, improve the sound source localization accuracy, suppress environmental noise, and improve the signal-to-noise ratio, thereby improving the comprehensiveness and accuracy of the detection process.

[0093] In some embodiments, continuous frame features of array acoustic signal data are extracted based on a preset unit sound frame time; based on the continuous frame features, the array acoustic signal data is framed to extract the time domain features, frequency domain features and time-frequency joint non-stationary features of the acoustic signal; based on the time domain features, frequency domain features and time-frequency joint non-stationary features of the acoustic signal, the mechanical vibration acoustic signal and the local discharge acoustic signal in the array acoustic signal data are separated according to the mechanical vibration acoustic features and the local discharge acoustic features; based on the local discharge acoustic signal, acoustic signal feature information is constructed; the mechanical vibration acoustic features are characterized by being dominated by low-frequency harmonic groups and exhibiting periodic attenuation characteristics; the local discharge acoustic features are characterized by high-frequency pulse clusters and having random burst characteristics.

[0094] The preset unit sound frame time may be a preset unit time length for dividing a time frame, such as 20ms;

[0095] The continuous frame feature may be a sound frame set obtained by dividing the continuous sound signal into frames according to a preset unit sound frame time.

[0096] The time domain characteristics of the acoustic signal can be characteristic parameters that describe the statistical characteristics of the acoustic wave in the time dimension, and are used to characterize the instantaneous energy changes and periodic laws of the acoustic signal.

[0097] The frequency domain characteristics of an acoustic signal can be characteristic parameters that describe the statistical properties of an acoustic wave in the frequency dimension, and are used to reveal the distribution patterns of different frequency components in an acoustic signal.

[0098] The time-frequency joint non-stationary feature can be a characteristic parameter that combines the time and frequency dimensions to analyze the dynamic changes of the acoustic signal, and is used to characterize the transient pulse and frequency modulation phenomena in the acoustic signal.

[0099] The mechanical vibration acoustic characteristics may be characteristics of acoustic signals generated by the operating vibration of mechanical parts of the equipment.

[0100] The partial discharge acoustic characteristics may be acoustic signal characteristics generated by abnormal partial discharge inside the device.

[0101] The periodic attenuation characteristic may be a feature in which the intensity of the sound signal shows a tendency to attenuate within a period.

[0102] A high-frequency pulse cluster can be a high-frequency, high-energy transient pulse that appears continuously in a short period of time in a sound signal.

[0103] Random burst characteristics can be characterized by sudden changes in the intensity of the sound signal within a short period of time.

[0104] Specifically, the acoustic signals of high-voltage electrical equipment have significant non-stationarity (such as bursts of discharge pulses and periodic fluctuations of mechanical vibration). Traditional full-time analysis will blur the characteristics of transient acoustic signals. By dividing long-time signals into short time periods (such as 20ms / frame), local features of different frames can be extracted to achieve frame processing. For example, the duration of local discharge pulses is usually in the microsecond level and only appears in a few frames. Frame processing can accurately capture their occurrence time and spatial distribution to avoid confusion with the steady-state signal of mechanical vibration. If the vibration caused by the operation of the equipment itself is confused with the abnormal local discharge, it is easy to cause invalid maintenance or delayed repairs due to misjudgment. The multi-channel array acoustic signal is divided into continuous frames with a frame length of 20ms and a 50% overlap rate. A Hanning window is added to each frame data to reduce spectral leakage. The timestamp and spatial coordinates of each frame data are marked (according to the geometric relationship of the microphone array). A time-space aligned frame data set is constructed to achieve frame processing of the array acoustic signal data, and then the root mean square energy, zero-crossing rate, and short-time average amplitude of each frame signal are quantified to generate The time domain feature vector is used as the time domain feature of the acoustic signal; a fast Fourier transform is performed on each frame of the acoustic signal to extract the frequency and amplitude of the harmonic component and the energy proportion of the high frequency band (10kHz-40kHz), and a frequency domain feature vector is generated as the frequency domain feature of the acoustic signal; a multi-layer wavelet packet decomposition is performed on each frame of the acoustic signal to quantify the energy entropy and instantaneous frequency variance of each subband, and a time-frequency feature vector is generated as the joint time-frequency non-stationary feature; the above time domain feature vector, frequency domain feature vector, and time-frequency feature vector are spliced ​​into a high-dimensional joint feature vector, and the high-dimensional joint feature vector is input into a pre-trained support vector machine classifier model (the training data contains labeled mechanical vibration and partial discharge acoustic signal samples, and the labeling is based on the mechanical vibration acoustic features and partial discharge acoustic features). Each frame of the signal is binary classified to achieve the separation of the mechanical vibration acoustic signal and the partial discharge acoustic signal in the array acoustic signal data to avoid confusion between the two signals. Based on the separated partial discharge acoustic signal, acoustic signal feature information is constructed so that the acoustic signal feature information points to the abnormal discharge situation inside the equipment.

[0105] Through this solution, the array acoustic signal data is framed and processed, and the time domain features, frequency domain features and time-frequency joint non-stationary features of the acoustic signal are extracted respectively. On this basis, the mechanical vibration acoustic signal and the partial discharge acoustic signal in the array acoustic signal data are separated according to the mechanical vibration acoustic characteristics and the partial discharge acoustic characteristics. Based on the partial discharge acoustic signal, the acoustic signal feature information is constructed so that the acoustic signal feature information points to the abnormal discharge situation inside the equipment, avoiding the confusion between the vibration caused by the operation of the equipment itself and the partial discharge anomaly, and preventing invalid maintenance or delayed repairs due to misjudgment.

[0106] In some embodiments, the layered structure parameter set includes structural layer thickness distribution information, structural material information, and geometric topology information; the insulating medium parameter set includes medium type, medium dynamic viscosity coefficient, medium sound speed propagation characteristics, and medium pressure reference.

[0107] The structural layer thickness distribution information may be information describing the thickness values ​​and spatial distribution characteristics of each layer structure of high-voltage equipment (such as transformer winding insulation paper layer, GIS shell metal layer).

[0108] The structural material information may be information describing the material types (such as epoxy resin, aluminum alloy) and their physical properties constituting each layer of the device structure.

[0109] The geometric topology information may be information that characterizes the connection relationship and shape parameters of each structural layer in the three-dimensional space of the device.

[0110] The medium type can be the specific type of insulating gas inside the high-voltage electrical equipment (such as SF6 gas, silicone oil).

[0111] The dynamic viscosity coefficient of the medium can be a quantitative indicator to describe the flow resistance characteristics of the insulating medium.

[0112] The medium sound velocity propagation characteristic may be the propagation speed of sound waves in an insulating medium.

[0113] The medium pressure reference can be the standard working pressure of the internal insulating medium of the high-voltage electrical equipment when it is in operation.

[0114] Specifically, the interior of high-voltage electrical equipment (such as enclosed gas-insulated switches and transformers) is composed of multiple layers of heterogeneous materials. Sound waves will experience multiple reflections, transmissions and attenuations during the propagation process. When the partial discharge acoustic signal passes through the layered structure inside the high-voltage electrical equipment, its energy attenuation degree is directly related to the structural material properties. The acoustic impedance of different materials (such as metals and polymers) is significantly different. On this basis, the propagation of the acoustic signal is also affected by the thickness and geometric shape (such as cavity) of the corresponding material. By collecting the structural layer thickness distribution information, structural material information and geometric topology information, the influence of the internal layered structure of the high-voltage electrical equipment on the partial discharge acoustic signal is fully reflected. The influence of discharge acoustic signals; the insulating medium is filled between different hierarchical structures inside high-voltage electrical equipment and is on the propagation path of local discharge acoustic signals. There are significant differences in the speed of sound propagation in insulating media with different characteristics. The sound absorption mechanisms of gases (such as SF6) and liquids (such as transformer oil) are significantly different. The viscosity of the insulating medium will cause phase delay when the sound wave propagates, and the change in medium pressure will change the acoustic impedance and attenuation coefficient. By clarifying the medium type, medium dynamic viscosity coefficient, medium sound speed propagation characteristics and medium pressure benchmark, a reliable data basis can be provided for a comprehensive analysis of the impact of insulating media on acoustic signals.

[0115] Through this scheme, a layered structure parameter set is constructed based on the structural layer thickness distribution information, structural material information and geometric topology information. The influence of the multi-layer structure inside high-voltage electrical equipment on the partial discharge acoustic signal is reflected from the three dimensions of material properties, material thickness and geometric shape. At the same time, an insulating medium parameter set is constructed based on the medium type, medium dynamic viscosity coefficient, medium sound speed propagation characteristics and medium pressure benchmark, providing a reliable data basis for a comprehensive analysis of the influence of insulating media on acoustic signals.

[0116] In some embodiments, according to the layered structure parameter set, a physical field simulation model of sound propagation based on a multi-layer geometric structure is constructed; according to the physical field simulation model, the reflection-transmission attenuation coefficient of the local discharge acoustic signal in different layered structures is determined; according to the insulating medium parameter set, the propagation path of the local discharge acoustic signal is phase compensated and corrected to determine the dielectric absorption coefficient; according to the reflection-transmission attenuation coefficient and the dielectric absorption coefficient, the local discharge acoustic signal is targetedly compensated and corrected to determine abnormal soundprint feature information.

[0117] The physical field simulation model can be a numerical model of multi-layer medium sound propagation constructed based on the finite element method, integrating structural geometry, material properties and boundary conditions, and is used to fit the propagation laws of sound waves in complex equipment.

[0118] The reflection-transmission attenuation coefficient can be used as a quantitative indicator to quantify the energy loss of acoustic waves at the layered interface.

[0119] Phase compensation correction can be a sound signal correction and repair process for the sound wave phase distortion caused by medium viscosity and inhomogeneity.

[0120] The medium absorption coefficient can be a normalized quantitative indicator that characterizes the intensity of the medium's absorption of sound wave energy.

[0121] Specifically, the layered structure parameter set is imported into a physical field modeling tool, such as the COMSOL Multiphysics acoustics module. An adaptive mesh is then created based on the geometric topology information. The acoustic impedance parameters corresponding to the structural material information are loaded at the interface of each layer of the structure to construct a physical field simulation model. The propagation state of the partial discharge acoustic signal in different layered structures is simulated using the physical field simulation model, and the reflection-transmission attenuation coefficient, which is used to characterize the attenuation effect of the partial discharge acoustic signal propagating in the layered structure, is quantified. Based on the properties of different media types, the insulating medium parameter set is input into the corresponding model (e.g., the Stokes model in fluid mechanics is used for gas insulating media, and the Wood model is used for liquid insulating media). The propagation path characteristics of the partial discharge acoustic signal in the insulating medium are simulated, and the dielectric absorption coefficient reflecting the influence of the insulating medium on the acoustic signal propagation is determined. The partial discharge acoustic signal is subjected to time-frequency decomposition, and the acoustic signal phase is inversely corrected based on the reflection-transmission attenuation coefficient and the dielectric absorption coefficient corresponding to the propagation path. The pure discharge soundprint is reconstructed, and the pure discharge soundprint is compared with the soundprint information obtained from experiments without partial discharge anomalies to extract abnormal soundprint feature information.

[0122] Through this scheme, a physical field simulation model is constructed based on the layered structure parameter set to simulate the negative impact of the acoustic signal during the propagation process between different layered structures inside the high-voltage electrical equipment, and the corresponding reflection-transmission attenuation coefficient is fitted. Based on the insulating medium parameter set, the propagation characteristics of the acoustic signal in the insulating medium are analyzed, and the dielectric absorption coefficient reflecting the influence of the insulating medium on the propagation of the acoustic signal is fitted. The attenuation characteristics of the acoustic signal under the dual influence are characterized by the reflection-transmission attenuation coefficient and the dielectric absorption coefficient, so as to reversely deduce the actual sound signal characteristics caused by partial discharge, accurately locate the abnormal soundprint feature information, and improve the accuracy of the judgment of local abnormal discharge.

[0123] In some embodiments, a three-dimensional space grid model is constructed based on the thickness distribution information and geometric topology information of the structural layer, the geometric characteristics of each layer of the structure are parameterized, and several hierarchical grid parameter nodes are determined; based on the structural material information, the acoustic impedance parameters of the corresponding structural material are loaded at each hierarchical grid parameter node, and according to the acoustic impedance parameters, the time delay characteristics, attenuation characteristics and superposition characteristics of the local discharge acoustic signal in each propagation path are simulated and marked by a ray tracing algorithm to construct a physical field simulation model.

[0124] The three-dimensional space mesh model can be a numerical model that discretizes the geometric structure of the device into finite element units for use in sound field simulation.

[0125] Hierarchical mesh parameter nodes can be key nodes in the mesh model that mark the intersection of each structural layer and are used to load material properties and acoustic boundary conditions.

[0126] The acoustic impedance parameter can be the product of material density and sound velocity, which characterizes the reflection / transmission characteristics of sound waves at the medium interface.

[0127] A ray tracing algorithm can be an algorithm that simulates the propagation path of sound waves and quantifies the reflection, transmission, and attenuation processes of sound waves in complex structures. The ray tracing algorithm can be implemented using the high-frequency approximation algorithm module in professional acoustic simulation software (such as PZFlex or Actran).

[0128] The delay characteristic can be the difference in the propagation time of the sound wave from the discharge source to the microphone array.

[0129] The attenuation characteristic can be the energy loss rate of the sound wave due to medium absorption and interface reflection during propagation.

[0130] The superposition feature can be the superposition interference effect of multipath sound waves (such as reflected waves and direct waves) at the receiving point.

[0131] Specifically, based on the thickness distribution information and geometric topology information of the structural layer, high-order tetrahedral elements are used for unstructured mesh division to ensure the mesh quality in areas with complex curvature, and a three-dimensional spatial mesh model containing hierarchical mesh parameter nodes is generated. According to the structural material information associated with the hierarchical mesh parameter nodes, the acoustic impedance parameters are marked to the corresponding hierarchical mesh parameter nodes. By randomly generating local discharge points and taking this as the starting point, the ray tracing algorithm is used to simulate and count the time delay characteristics, attenuation characteristics and superposition characteristics of the local discharge acoustic signals emitted by the local discharge points in each propagation path, and a physical field simulation model for characterizing the propagation characteristics of the local discharge acoustic signals is constructed.

[0132] Through this scheme, a three-dimensional spatial grid model containing hierarchical grid parameter nodes is constructed according to the structural layer thickness distribution information and geometric topology information, so as to realize the sound field simulation of the three-dimensional irregular structure inside the high-voltage electrical equipment and eliminate the sound source positioning offset caused by the two-dimensional model. On this basis, based on the acoustic impedance parameters reflected in the structural material information, the time delay characteristics, attenuation characteristics and superposition characteristics of the partial discharge acoustic signal in each propagation path are simulated and marked through the ray tracing algorithm, and a physical field simulation model is constructed. The high-precision simulation of the sound wave propagation characteristics under the complex structure of the high-voltage equipment is realized, which provides a reliable numerical basis for the physical field compensation of abnormal soundprint characteristics and significantly improves the positioning accuracy and diagnostic reliability of partial discharge detection.

[0133] In some embodiments, a basic dynamic propagation velocity field model of a partial discharge acoustic signal in an insulating medium is constructed according to the medium type and the medium sound speed propagation characteristics; based on the basic dynamic propagation velocity field model, the viscous phase delay of the partial discharge acoustic signal in the insulating medium is simulated according to the medium dynamic viscosity coefficient and the medium pressure reference; the viscous phase delay is positively correlated with the medium dynamic viscosity coefficient; the viscous phase delay is negatively correlated with the medium pressure reference; the viscous phase delay is normalized to determine the medium absorption coefficient.

[0134] The basic dynamic propagation velocity field model can be a numerical model that describes the spatial distribution of the propagation velocity of sound waves in an inhomogeneous medium.

[0135] Viscous phase delay of acoustic waves can be caused by the propagation time delay of the medium due to viscous resistance.

[0136] Specifically, the sound velocity calculation model is selected according to the medium type: the gas medium is based on the modified ideal gas equation, and the liquid medium is based on the Tait state equation. The experimental data of the medium sound velocity propagation characteristics (obtained through sound propagation experiments under different insulating media) are imported, and the model parameters are fitted by the least squares method to construct a basic dynamic propagation velocity field model; based on the basic dynamic propagation velocity field model, the medium dynamic viscosity coefficient and the medium pressure benchmark are introduced to simulate the viscous phase delay of the partial discharge acoustic signal under the influence of the viscosity and pressure of the insulating medium. The specific benchmark is that the greater the viscosity of the insulating medium, the greater the corresponding viscous phase delay. According to the positive correlation coefficient between the viscosity of the insulating medium and the viscous phase delay, the conversion is performed. The greater the pressure of the insulating medium, the lower the corresponding viscous phase delay. According to the negative correlation coefficient between the pressure of the insulating medium and the viscous phase delay, the conversion is performed. After the above positive and negative adjustments, the viscous phase delay of the partial discharge acoustic signal in the insulating medium is obtained. This is used to characterize the intensity of the absorption effect of the sound signal when passing through the current insulating medium. The minimum-maximum normalization algorithm is further used to normalize the viscous phase delay, and the quantified dielectric absorption coefficient is mapped to the numerical range of (0,1).

[0137] Through this solution, a basic dynamic propagation velocity field model is constructed based on the medium type and the sound speed propagation characteristics of the medium to reflect the basic propagation characteristics of the sound signal in the current insulating medium. On this basis, the dynamic viscosity coefficient of the medium and the medium pressure reference are introduced to simulate the viscous phase delay of the partial discharge sound signal under the dual influence of the viscosity and pressure of the insulating medium. The viscous phase delay is normalized to obtain the medium absorption coefficient to accurately reflect the actual propagation state of the sound signal in the insulating medium and improve the accuracy of subsequent positioning analysis of the partial discharge position.

[0138] In some embodiments, after determining several levels of grid parameter nodes in the physical field simulation model, the reflection-transmission attenuation coefficient and the medium absorption coefficient are substituted into the inverse ray tracing algorithm to invert the sound source propagation path, determine the coordinate point of the sound source of the local discharge sound signal in the three-dimensional space grid model, and generate the three-dimensional coordinates of the abnormal position; based on the geometric topology information, the relative position of the abnormal equipment component and the local discharge is determined according to the three-dimensional coordinates of the abnormal position; according to the relative position of the abnormal equipment component and the local discharge, the preset equipment abnormality information library is retrieved to determine the abnormality troubleshooting suggestions; according to the abnormal equipment component, the relative position of the local discharge and the abnormality troubleshooting suggestions, the abnormal component information is constructed.

[0139] The inverse ray tracing algorithm may be an algorithm for tracing the sound wave propagation path in reverse from the microphone array receiving point to the partial discharge location.

[0140] Inverse sound source propagation path may be a process of reversely deducing the sound signal propagation path to locate the sound source.

[0141] The three-dimensional coordinates of the abnormal position may be spatial coordinates for locating a partial discharge source in a three-dimensional model of the device.

[0142] The abnormal equipment component may be the specific part where the partial discharge occurs.

[0143] The relative position of the partial discharge may be the relative position of a specific discharge position in the corresponding abnormal equipment component.

[0144] The preset equipment anomaly information database may be a knowledge base storing historical defect cases, including typical discharge locations, fault types, and corresponding anomaly troubleshooting suggestions.

[0145] Abnormal troubleshooting suggestions can be recommended maintenance measures based on the current abnormal characteristics.

[0146] Specifically, based on the current position of the microphone array, the reflection-transmission attenuation coefficient and the dielectric absorption coefficient are loaded into the physical field simulation model, and the inverse ray tracing algorithm is run. According to the characteristics of the currently collected sound signal, the sound source propagation path is reversely deduced, and the sound source corresponding to the current sound signal inside the high-voltage electrical equipment is located. Then, the coordinate point of the sound source of the partial discharge sound signal in the three-dimensional space grid model is determined, and the three-dimensional coordinates of the abnormal position are generated. The equipment component at the three-dimensional coordinates of the abnormal position is the abnormal equipment component. Based on the spatial grid corresponding to the abnormal equipment component, a new spatial coordinate system is established to determine the relative position of the partial discharge. According to the abnormal equipment component and the relative position of the partial discharge, the preset equipment abnormality information database is retrieved to determine the abnormal troubleshooting suggestions that can be used by maintenance personnel in the event of abnormal discharge at the current relative position of the partial discharge. By integrating the abnormal equipment component, the relative position of the partial discharge and the abnormal troubleshooting suggestions, the abnormal component information is constructed.

[0147] Through this solution, based on the physical field simulation model, according to the reflection-transmission attenuation coefficient and the dielectric absorption coefficient, the inverse ray tracing algorithm is used to deduce the propagation path of the currently collected partial discharge acoustic signal, and then locate the sound source of the partial discharge acoustic signal inside the high-voltage electrical equipment, and obtain the three-dimensional coordinates of the abnormal position. Combined with the geometric topology information, the relative position of the abnormal equipment component and the partial discharge is determined. In this way, the preset equipment abnormality information database is retrieved, and abnormality troubleshooting suggestions are determined. According to the abnormal equipment components, the relative position of the partial discharge and the abnormality troubleshooting suggestions, the abnormal component information is constructed to achieve accurate positioning of the abnormal discharge position inside the high-voltage electrical equipment, and provide corresponding abnormality troubleshooting suggestions, effectively improving the inspection and maintenance efficiency and effectiveness of subsequent maintenance personnel.

[0148] In some embodiments, maintenance personnel maintenance feedback information is obtained, the maintenance personnel maintenance feedback information is analyzed, and it is determined whether the maintenance personnel adopts the abnormality troubleshooting suggestion; if the maintenance personnel adopts the corresponding abnormality troubleshooting suggestion, the influence factor of the abnormality troubleshooting suggestion is increased; if the maintenance personnel does not adopt the corresponding abnormality troubleshooting suggestion, the troubleshooting process in the maintenance personnel maintenance feedback information is included in the troubleshooting suggestion list corresponding to the relative position of the partial discharge under the corresponding abnormal equipment component in the preset equipment abnormality information library, and its corresponding influence factor is set to the preset influence baseline value; each abnormality troubleshooting suggestion in the troubleshooting suggestion list is sorted according to the value of its corresponding influence factor.

[0149] The maintenance personnel's maintenance feedback information may be a text record or structured form data submitted by the maintenance personnel through a mobile terminal after on-site maintenance.

[0150] The impact factor may be a weighted value that quantitatively represents the historical effectiveness of the troubleshooting suggestion.

[0151] The troubleshooting suggestion list may be a set of maintenance plans generated for the current partial discharge anomaly and sorted by influencing factors.

[0152] The preset impact baseline value can be the initial impact factor for newly added unverified suggestions.

[0153] Specifically, since the partial discharge anomalies of high-voltage electrical equipment are affected by the coupling of many different influencing factors, the anomaly troubleshooting suggestions constructed based on historical experience and expert experience cannot fully cover actual anomaly situations. Based on the collected maintenance personnel's maintenance feedback information, the adjustment mechanism of the influencing factors is utilized to dynamically update the anomaly troubleshooting suggestions in the anomaly troubleshooting suggestion list and adjust the recommendation priority. A complete closed loop of "suggestion generation-field verification-knowledge evolution" is established, so that the anomaly troubleshooting system has the ability to continuously self-optimize to adapt to complex actual situations and further improve the maintenance efficiency and maintenance effect of maintenance personnel.

[0154] Through this solution, based on the maintenance personnel's feedback information collected and utilizing the adjustment mechanism of influencing factors, the abnormality troubleshooting suggestions in the abnormality troubleshooting suggestion list are dynamically updated and the recommendation priority is adjusted. A complete closed loop of "suggestion generation-field verification-knowledge evolution" is established, which enables the abnormality troubleshooting system to have the ability to continuously self-optimize to adapt to complex actual situations and further improve the maintenance efficiency and maintenance results of maintenance personnel.

[0155] Figure 3 A schematic diagram of a high-voltage electrical equipment inspection system based on microphone array measurement is provided in one embodiment of the present application. Figure 3 As shown, a high-voltage electrical equipment inspection system 300 based on microphone array measurement in this embodiment includes: a feature analysis module 301 , a feature correction module 302 and an anomaly location module 303 .

[0156] A feature analysis module 301 is configured to obtain array acoustic signal data, analyze the array acoustic signal data, and determine acoustic signal feature information;

[0157] A feature correction module 302 is configured to obtain a layered structure parameter set and an insulating medium parameter set of the target electrical device, and perform targeted compensation and correction on the acoustic signal feature information based on the layered structure parameter set and the insulating medium parameter set to determine abnormal voiceprint feature information;

[0158] The abnormality locating module 303 is configured to generate abnormal component information based on the abnormal voiceprint feature information, and determine and output an abnormality detection report.

[0159] Optionally, the array acoustic signal data in the feature analysis module 301 is obtained through a ring microphone array;

[0160] The number of microphones in the annular microphone array is not less than 128;

[0161] The acoustic measurement frequency range of the annular microphone array is 2 kHz to 40 kHz.

[0162] Optionally, the feature analysis module 301 is specifically configured to:

[0163] According to the continuous frame features of the array acoustic signal data, the array acoustic signal data is subjected to frame processing to extract the acoustic signal time domain features, the acoustic signal frequency domain features and the time-frequency joint non-stationary features;

[0164] Based on the acoustic signal time domain features, the acoustic signal frequency domain features and the time-frequency joint non-stationary features, and according to the mechanical vibration acoustic features and the partial discharge acoustic features, the mechanical vibration acoustic signal and the partial discharge acoustic signal in the array acoustic signal data are separated;

[0165] constructing the acoustic signal characteristic information according to the partial discharge acoustic signal;

[0166] The mechanical vibration acoustic characteristics are characterized by being dominated by low-frequency harmonic groups and exhibiting periodic attenuation characteristics;

[0167] The local discharge acoustic characteristics are manifested as high-frequency pulse clusters and have random burst characteristics.

[0168] Optionally, the layered structure parameter set in the feature correction module 302 includes structure layer thickness distribution information, structure material information, and geometric topology information;

[0169] The insulating medium parameter set includes medium type, medium dynamic viscosity coefficient, medium sound velocity propagation characteristics and medium pressure reference.

[0170] Optionally, the feature correction module 302 is specifically configured to:

[0171] Constructing a physical field simulation model of sound propagation based on multi-layer geometric structures according to the layered structure parameter set;

[0172] determining the reflection-transmission attenuation coefficient of the partial discharge acoustic signal in different layered structures according to the physical field simulation model;

[0173] performing phase compensation correction on the propagation path of the partial discharge acoustic signal according to the insulating medium parameter set to determine the dielectric absorption coefficient;

[0174] According to the reflection-transmission attenuation coefficient and the medium absorption coefficient, targeted compensation and correction are performed on the partial discharge acoustic signal to determine the abnormal voiceprint feature information.

[0175] Optionally, when constructing a physical field simulation model based on multi-layer geometric structure sound propagation according to the layered structure parameter set, the feature correction module 302 is specifically configured to:

[0176] Constructing a three-dimensional spatial grid model based on the thickness distribution information of the structural layer and the geometric topology information, parametrically characterizing the geometric features of each layer of the structure, and determining a plurality of hierarchical grid parameter nodes;

[0177] Based on the structural material information, the acoustic impedance parameters of the corresponding structural material are loaded at each of the hierarchical grid parameter nodes. According to the acoustic impedance parameters, the time delay characteristics, attenuation characteristics, and superposition characteristics of the partial discharge acoustic signal in each propagation path are simulated and marked by a ray tracing algorithm to construct the physical field simulation model.

[0178] Optionally, the feature correction module 302 performs phase compensation correction on the propagation path of the partial discharge acoustic signal according to the insulating medium parameter set to determine the dielectric absorption coefficient, specifically for:

[0179] Constructing a basic dynamic propagation velocity field model of the partial discharge acoustic signal in the insulating medium according to the medium type and the sound velocity propagation characteristics of the medium;

[0180] Based on the basic dynamic propagation velocity field model, according to the medium dynamic viscosity coefficient and the medium pressure reference, simulating the viscous phase delay of the partial discharge acoustic signal in the insulating medium;

[0181] The viscous phase delay is positively correlated with the dynamic viscosity coefficient of the medium;

[0182] The viscous phase delay is negatively correlated with the medium pressure reference;

[0183] The viscous phase delay is normalized to determine the medium absorption coefficient.

[0184] Optionally, the anomaly locating module 303 is specifically configured to:

[0185] After determining several levels of grid parameter nodes in the physical field simulation model, substituting the reflection-transmission attenuation coefficient and the medium absorption coefficient into an inverse ray tracing algorithm, inverting the sound source propagation path, determining the coordinate point of the sound source of the partial discharge sound signal in the three-dimensional space grid model, and generating the three-dimensional coordinates of the abnormal position;

[0186] Based on the geometric topology information and the three-dimensional coordinates of the abnormal position, determining the relative position of the abnormal equipment component and the partial discharge;

[0187] According to the relative position of the abnormal equipment component and the partial discharge, a preset equipment abnormality information database is retrieved to determine abnormality troubleshooting suggestions;

[0188] The abnormal component information is constructed based on the abnormal equipment component, the relative position of the partial discharge and the abnormality troubleshooting suggestion.

[0189] Optionally, the microphone array measurement-based high-voltage electrical equipment inspection system 300 further includes a suggestion adjustment module 304 for:

[0190] Obtain maintenance personnel's maintenance feedback information, analyze the maintenance personnel's maintenance feedback information, and determine whether the maintenance personnel adopt the abnormality troubleshooting suggestions;

[0191] If the maintenance personnel adopt the corresponding abnormality troubleshooting suggestion, then the impact factor of the abnormality troubleshooting suggestion is increased;

[0192] If the maintenance personnel does not adopt the corresponding abnormality troubleshooting suggestion, the troubleshooting process in the maintenance personnel's maintenance feedback information is included in the troubleshooting suggestion list corresponding to the relative position of the partial discharge under the abnormal equipment component in the preset equipment abnormality information database, and the corresponding impact factor is set as a preset impact baseline value;

[0193] The abnormality troubleshooting suggestions in the troubleshooting suggestion list are sorted according to the numerical values ​​of their corresponding impact factors.

[0194] The system of this embodiment can be used to execute the method of any of the above embodiments. Its implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A high-voltage electrical equipment inspection method based on microphone array measurement, characterized in that: include: Acquiring array acoustic signal data of a target electrical device, analyzing the array acoustic signal data, and determining acoustic signal characteristic information; The acoustic signal feature information is a feature set extracted from the array acoustic signal data and used to characterize the operating state of the target device; Obtaining a layered structure parameter set and an insulating medium parameter set of the target electrical device, and performing targeted compensation and correction on the acoustic signal characteristic information based on the layered structure parameter set and the insulating medium parameter set to determine abnormal voiceprint characteristic information; The abnormal voiceprint feature information is sound feature information used to map the local abnormal discharge situation inside the target electrical equipment; Generate abnormal component information based on the abnormal voiceprint feature information, and determine and output an abnormal detection report; The array acoustic signal data is obtained through a ring microphone array; The number of microphones in the annular microphone array is not less than 128; The acoustic measurement frequency range of the annular microphone array is 2 kHz to 40 kHz; The analyzing the array acoustic signal data to determine acoustic signal characteristic information includes: Extracting continuous frame features of the array acoustic signal data according to a preset unit sound frame time; According to the continuous frame features, the array acoustic signal data is framed to extract the acoustic signal time domain features, acoustic signal frequency domain features and time-frequency joint non-stationary features; Based on the acoustic signal time domain features, the acoustic signal frequency domain features and the time-frequency joint non-stationary features, and according to the mechanical vibration acoustic features and the partial discharge acoustic features, the mechanical vibration acoustic signal and the partial discharge acoustic signal in the array acoustic signal data are separated; constructing the acoustic signal characteristic information according to the partial discharge acoustic signal; The mechanical vibration acoustic characteristics are characterized by being dominated by low-frequency harmonic groups and exhibiting periodic attenuation characteristics; The local discharge acoustic characteristics are manifested as high-frequency pulse clusters and have random burst characteristics.

2. The method according to claim 1, characterized in that The layered structure parameter set includes structure layer thickness distribution information, structure material information and geometric topology information; The insulating medium parameter set includes medium type, medium dynamic viscosity coefficient, medium sound velocity propagation characteristics and medium pressure reference.

3. The method according to claim 2, characterized in that The performing targeted compensation and correction on the acoustic signal characteristic information based on the layered structure parameter set and the insulating medium parameter set to determine abnormal voiceprint characteristic information includes: Constructing a physical field simulation model of sound propagation based on multi-layer geometric structures according to the layered structure parameter set; determining the reflection-transmission attenuation coefficient of the partial discharge acoustic signal in different layered structures according to the physical field simulation model; performing phase compensation correction on the propagation path of the partial discharge acoustic signal according to the insulating medium parameter set to determine the dielectric absorption coefficient; According to the reflection-transmission attenuation coefficient and the medium absorption coefficient, targeted compensation and correction are performed on the partial discharge acoustic signal to determine the abnormal voiceprint feature information.

4. The method according to claim 3, characterized in that The method of constructing a physical field simulation model based on multi-layer geometric structure sound propagation according to the layered structure parameter set includes: Constructing a three-dimensional spatial grid model based on the thickness distribution information of the structural layer and the geometric topology information, parametrically characterizing the geometric features of each layer of the structure, and determining a plurality of hierarchical grid parameter nodes; Based on the structural material information, the acoustic impedance parameters of the corresponding structural material are loaded at each of the hierarchical grid parameter nodes. According to the acoustic impedance parameters, the time delay characteristics, attenuation characteristics, and superposition characteristics of the partial discharge acoustic signal in each propagation path are simulated and marked by a ray tracing algorithm to construct the physical field simulation model.

5. The method according to claim 3, characterized in that The performing phase compensation correction on the propagation path of the partial discharge acoustic signal according to the insulating medium parameter set to determine the dielectric absorption coefficient includes: Constructing a basic dynamic propagation velocity field model of the partial discharge acoustic signal in the insulating medium according to the medium type and the sound velocity propagation characteristics of the medium; Based on the basic dynamic propagation velocity field model, according to the medium dynamic viscosity coefficient and the medium pressure reference, simulating the viscous phase delay of the partial discharge acoustic signal in the insulating medium; The viscous phase delay is positively correlated with the dynamic viscosity coefficient of the medium; The viscous phase delay is negatively correlated with the medium pressure reference; The viscous phase delay is normalized to determine the medium absorption coefficient.

6. The method according to claim 5, characterized in that The generating of abnormal component information according to the abnormal voiceprint feature information includes: After determining several levels of grid parameter nodes in the physical field simulation model, substituting the reflection-transmission attenuation coefficient and the medium absorption coefficient into an inverse ray tracing algorithm, inverting the sound source propagation path, determining the coordinate point of the sound source of the partial discharge sound signal in the three-dimensional space grid model, and generating the three-dimensional coordinates of the abnormal position; Based on the geometric topology information and the three-dimensional coordinates of the abnormal position, determining the relative position of the abnormal equipment component and the partial discharge; According to the relative position of the abnormal equipment component and the partial discharge, a preset equipment abnormality information database is retrieved to determine abnormality troubleshooting suggestions; The abnormal component information is constructed based on the abnormal equipment component, the relative position of the partial discharge and the abnormality troubleshooting suggestion.

7. The method according to claim 6, characterized in that The method further comprises: Obtain maintenance personnel's maintenance feedback information, analyze the maintenance personnel's maintenance feedback information, and determine whether the maintenance personnel adopt the abnormality troubleshooting suggestions; If the maintenance personnel adopt the corresponding abnormality troubleshooting suggestion, then the impact factor of the abnormality troubleshooting suggestion is increased; If the maintenance personnel does not adopt the corresponding abnormality troubleshooting suggestion, the troubleshooting process in the maintenance personnel's maintenance feedback information is included in the troubleshooting suggestion list corresponding to the relative position of the partial discharge under the abnormal equipment component in the preset equipment abnormality information database, and the corresponding impact factor is set as a preset impact baseline value; The abnormality troubleshooting suggestions in the troubleshooting suggestion list are sorted according to the numerical values ​​of their corresponding impact factors.

8. A high-voltage electrical equipment inspection system based on microphone array measurement, characterized in that: The method as claimed in any one of claims 1 to 7 comprises: A feature analysis module, configured to acquire array acoustic signal data, analyze the array acoustic signal data, and determine acoustic signal feature information; a feature correction module, configured to obtain a layered structure parameter set and an insulating medium parameter set of the target electrical device, and to perform targeted compensation and correction on the acoustic signal feature information based on the layered structure parameter set and the insulating medium parameter set to determine abnormal voiceprint feature information; The abnormality positioning module is used to generate abnormal component information based on the abnormal voiceprint feature information, and determine and output an abnormality detection report.

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