Electric power equipment abnormal discharge detection method and system based on discharge area segmentation, medium and processor

By constructing a three-dimensional analysis framework of "time-domain dynamic features - frequency-domain fingerprint spectrum - spatial field strength distribution", and through multi-dimensional technologies of quantum sensors and holographic discharge imaging modules, the problems of high false detection rate and insufficient positioning accuracy in abnormal discharge detection of power equipment are solved, and efficient and accurate discharge area segmentation is achieved.

CN120870772APending Publication Date: 2025-10-31GUANGXI POWER GRID CORP
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Patent Information

Application Number
CN202511134639.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-08-14
Publication Date
2025-10-31

AI Technical Summary

Technical Problem

Existing technologies lack the ability to accurately segment and dynamically analyze discharge areas, resulting in a high false detection rate, insufficient automation, and inadequate accuracy in locating abnormal discharges in power equipment.

Method used

A method for detecting abnormal discharge in power equipment based on discharge region segmentation is adopted. By acquiring time-domain pulse information, pulse frequency-domain spectrum lines, and spatial coordinates, and combining them with holographic image data, a quantum sensing array and a holographic discharge imaging module are used to collect multi-dimensional information, extract and encode features, construct a three-dimensional model, and perform joint processing through a pulse convolutional neural network. The model is then verified by combining it with a historical fault database to achieve accurate segmentation of the discharge region.

Benefits of technology

It improves the accuracy and efficiency of abnormal discharge detection, can accurately locate the position of abnormal discharge, achieves sub-millimeter level precise segmentation, and saves communication resources through distributed architecture.

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Abstract

The invention provides a power equipment abnormal discharge detection method based on discharge region segmentation. The method comprises the steps of obtaining time domain pulse information, pulse frequency domain spectral lines, corresponding space coordinates and holographic image data; performing feature processing to obtain a pulse waveform code and a frequency domain map; performing space field intensity mapping to obtain three-dimensional discharge field intensity distribution; constructing a first three-dimensional model by using the holographic image data, and obtaining a plurality of nodes after segmentation; establishing a first incidence matrix, a second incidence matrix and a third incidence matrix, and determining corresponding weights; performing joint processing on each matrix and the corresponding weight to obtain a preliminary segmentation result of discharge; determining a target node with abnormal discharge based on the preliminary segmentation result and the information of each node; and verification is performed based on the fault information of the preliminary segmentation result and the target node, and if the verification is passed, the preliminary segmentation result is taken as the target segmentation result, so that the accuracy and efficiency of abnormal discharge detection are improved, and the position of abnormal discharge can be accurately positioned.
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