CN-122020057-A - Partial discharge positioning detection method and system based on combined detection of sound and electricity and multidimensional feature fusion

CN122020057ACN 122020057 ACN122020057 ACN 122020057ACN-122020057-A

Abstract

The invention discloses a partial discharge positioning detection method and system based on combined detection of sound and electricity and multidimensional feature fusion, and belongs to the technical field of intelligent power grid state detection. The invention uses ultra-high frequency (UHF) signals as discharge absolute time reference, adopts a red pool information quantity criterion (AIC) to self-adaptively pick up ultrasonic wave microwave heads, overcomes the failure problem of the traditional threshold method under low signal to noise ratio, constructs four-dimensional state vectors comprising space coordinates and equivalent sound velocity, solves by using a weighted Gaussian-Newton iterative algorithm, introduces a temperature field sound velocity correction model and a grid search initial value estimation algorithm, and solves the problems of iterative divergence and local optimal solution. In addition, the method integrates algorithm modules such as intelligent noise reduction, physical field self-adaptive correction, sound intensity auxiliary positioning and the like, and achieves high-precision and high-robustness positioning of the partial discharge source.

Inventors

TANG BOHAN
LUO YANG
LI ZHENSHUO
HUANG YUWEI
SUN BANG
YOU JINGREN
YU JUNYANG
CAO PENGXIANG

Assignees

汤博涵

Dates

Publication Date: 20260512
Application Date: 20260204

Claims (10)

1. The partial discharge positioning detection method based on the combined detection of sound and electricity and the multi-dimensional feature fusion is characterized by comprising the following steps: The intelligent noise reduction step comprises the steps of performing intelligent noise reduction on the ultrasonic signals, and specifically comprises the steps of determining the optimal decomposition layer number of variation modal decomposition by adopting an energy difference tracking method, performing self-adaptive optimization on penalty factors of modal components in the variation modal decomposition by adopting a longhorn beetle whisker search algorithm, and performing self-adaptive optimization on penalty factors based on the modal components Purifying the decomposed modal components by using a criterion and a residual noise suppression algorithm of a dynamic threshold function to obtain noise-reduced ultrasonic signals; the accurate wave head picking step is to self-adaptively pick up the wave head arrival time of each path of ultrasonic signals after noise reduction based on the red pool information quantity criterion by using the ultrahigh frequency signals as discharge absolute time references; acquiring temperature distribution data in the detection equipment, establishing a sound velocity correction model based on the temperature distribution data, and correcting the propagation speed of ultrasonic waves in a medium in real time; The space positioning calculation step comprises the steps of taking space coordinates and equivalent sound velocity of a discharge source as state variables, taking a difference value between the arrival time of the wave head and the absolute time of discharge as an observation value, constructing a positioning equation set, and solving the positioning equation set by adopting a weighted Gaussian-Newton iterative algorithm to obtain high-precision space coordinates of the discharge source, wherein a weight matrix is dynamically constructed according to the signal-to-noise ratio of each ultrasonic sensor signal.
2. The method according to claim 1, wherein the determining the optimal decomposition layer number of the variational modal decomposition by using an energy difference tracking method specifically comprises: The maximum decomposition layer number is preset And initial number of decomposition layers ; Pre-decomposing the original signal, and calculating the energy difference of the signal components between adjacent decomposition layers ; Gradually increasing the number of current decomposition layers Up to Greater than Selecting the energy difference The minimum number of layers is taken as the optimal decomposition number of layers.
3. The method of claim 1, wherein the adaptive optimization of penalty factors for each modal component in the variant modal decomposition by using a longhorn beetle whisker search algorithm comprises: maximizing the sum of kurtosis values of all modal components to be an objective function; And adjusting the searching direction and the step length by simulating a longicorn tentacle detection mechanism, and iteratively optimizing to obtain each layer of punishment factor combination which maximizes the objective function.
4. The method according to claim 1, wherein the adaptive pickup arrival time based on the red pool information volume criterion specifically comprises: For each path of ultrasonic discrete sequence, calculating each possible segmentation point in the sequence The AIC value is calculated according to the following formula: Wherein, the For the length of the sequence, Is in front of The variance of the individual sample points is calculated, Is the back of Variance of each sampling point, selecting and making The point corresponding to the global minimum is obtained as the arrival time of the wave head of the path signal.
5. The method according to claim 1, wherein in the physical field adaptive correction step, the establishing of the sound velocity correction model specifically includes: Acquiring oil temperature data of the top and the bottom of the detection equipment, and constructing a temperature gradient model in the vertical direction ; Based on empirical relationship between ultrasonic propagation velocity and temperature And a propagation path between the discharge source and the sensor, calculating an effective average sound speed by path integration for correcting a sound speed variable in the positioning equation set.
6. The method of claim 1, wherein the spatial location calculation step further comprises an iterative initial value estimation step of globally scanning a location space by using a grid search method before the weighted gauss-newton iteration starts, and selecting a rough coordinate as an iterative initial value of the state variable by using a residual square sum as a criterion.
7. The method of claim 1, further comprising the step of sound intensity assisted localization: Acquiring ultrasonic energy distribution information through a sound intensity sensor array, and estimating the direction of arrival of a sound source; Calculating an included angle between the primary coordinate direction obtained by the space positioning calculation step and the direction of arrival; And if the included angle is larger than a preset threshold, triggering sound intensity auxiliary optimization, constructing an objective function comprising an energy attenuation model and a sparse regularization term, performing iterative solution, and correcting and verifying the primary coordinates.
8. A partial discharge positioning detection system implementing the method of any one of claims 1 to 7, comprising: The intelligent noise reduction module is used for executing the intelligent noise reduction step and comprises an optimal decomposition layer number judging unit, a penalty factor optimizing unit and a residual noise suppression unit; the wave head picking and joint triggering module is used for executing the wave head accurate picking step and comprises a wave head picking unit based on AIC criteria; the physical field correction module is used for executing the physical field self-adaptive correction step and comprises a temperature gradient modeling unit and a sound velocity calculation unit; the core positioning resolving module is used for executing the space positioning resolving step and comprises a weighted least square modeling unit, a grid search initial value estimating unit and a weighted Gaussian-Newton iteration resolving unit; And the sound intensity auxiliary positioning module is used for executing the sound intensity auxiliary positioning step and comprises a direction-of-arrival estimation unit and a sound intensity-coordinate joint optimization unit.
9. The system of claim 8, further comprising a data preprocessing module and a result display module, wherein the data preprocessing module is connected between the signal acquisition module and the intelligent noise reduction module and is used for amplifying, filtering and synchronously aligning an original signal, and the result display module is connected with the core positioning resolving module and is used for visually outputting positioning coordinates, confidence and discharge intensity information.
10. The system of claim 8, wherein the intelligent noise reduction module, the wave head picking and joint triggering module, the physical field correction module, the core positioning and resolving module and the sound intensity auxiliary positioning module are integrated in an embedded processor, an industrial computer or a cloud server in a software algorithm mode.

Description

Partial discharge positioning detection method and system based on combined detection of sound and electricity and multidimensional feature fusion Technical Field The invention relates to the technical field of high-voltage insulation state detection and fault diagnosis, in particular to a method and a system for high-precision partial discharge positioning and type identification by combining ultrahigh-frequency electromagnetic waves and ultrasonic signals, which are applied to transformers, gas-insulated fully-closed combined electrical appliances and high-voltage cable accessories. Background Partial discharge is a pulsed discharge that produces a series of physical and chemical changes in the interior and surrounding space of the electrical device, such as light, sound, electrical and mechanical vibrations. These various physical and chemical changes associated with the partial discharge may provide a detection signal for detecting the internal insulation state of the electrical device. According to the detection principle and means, common partial discharge detection methods include an ultrasonic method, an ultrahigh frequency method and the like. But partial discharge (PARTIALDISCHARGE) is a major cause of insulation degradation of high-voltage power equipment. Timely and accurate discovery and positioning of PD sources is a key to preventing sudden failure of equipment. The UHF method has high detection frequency, high requirements on bandwidth, sampling rate and the like of detection system hardware, poor anti-interference and difficult accurate positioning in a complex structure, and the AE method has high anti-interference, but has high unknown number of equation sets based on time difference due to fast attenuation and incapability of acquiring 'absolute zero moment' of discharge, so that the solution is difficult, and the detection workload is high in field application. (2) Traditional ultrasonic detection mainly relies on a voltage threshold method to judge signal arrival. However, after the ultrasonic signals generated by the PD are attenuated by the multi-layer medium, the ultrasonic signals tend to be very weak when reaching the sensor and are submerged in background noise, the moment recognized by the threshold method is seriously delayed by the aid of the intensity, and the positioning error of the meter level is directly introduced. (3) the prior art patent mostly assumes that the medium sound velocity is constant. In fact, a significant temperature gradient exists in the large transformer, and the statistical temperature difference can be achieved through a large amount of dataThe sound velocity varies significantly with temperature, and a fixed sound velocity model can lead to systematic deviations. (4) The traditional Newton iteration method is sensitive to an initial value, and if the initial value is not properly selected, the algorithm is easy to diverge or converge to an error local extreme point. (5) The ultrasonic wave is reflected at the metal wall to form a secondary wave head, and a 'double solution' condition can occur in the time difference equation set. Therefore, there is a need for a combined acoustic and electric detection technique that incorporates higher order statistic signal processing, environmental adaptation correction, and robust optimization algorithms. Disclosure of Invention The invention aims to provide a partial discharge positioning detection method and system based on combined detection of sound and electricity and multidimensional feature fusion, which solve the problems of difficult extraction of weak signals, poor convergence of a positioning algorithm, large influence of environmental parameters and single diagnosis dimension in the prior art. In order to achieve the above purpose, the invention adopts the following technical scheme: A method and a system for detecting partial discharge by combined acoustic and electric partial discharge are designed, and mainly comprise an intelligent noise reduction module and a combined acoustic and electric signal positioning module. Furthermore, the intelligent noise reduction module is used as a key functional unit for partial discharge signal processing, integrates three core technologies of an optimal decomposition layer number judging algorithm, a penalty factor optimizing algorithm and a residual noise suppression algorithm, and cooperatively realizes efficient filtering of noise interference and accurate retention of discharge signal characteristics to form a 'decomposition-optimization-suppression' progressive noise reduction processing system. Preferably, the optimal decomposition layer number judgment algorithm of the invention adopts an energy difference tracking method to accurately determine the decomposition boundary. Firstly, setting the maximum decomposition layer number according to the characteristics of partial discharge signals and the decomposition timelinessAnd initializing an optimal decompo