电力系统保护与控制2025，Vol.53Issue(11)：51-62,12.DOI:10.19783/j.cnki.pspc.241176
基于声光融合成像特征解析的电力设备局部放电精细识别方法研究
Refined identification method for partial discharge in power equipment based on acoustic-optical fusion imaging feature analysis
摘要
Abstract
Partial discharge is an important indicator for assessing the insulation condition of power equipment,and accurate identification of partial discharge types is essential for ensuring the safe operation of both power equipment and power grid.However,due to weak partial discharge signals and the similar characteristics of difference types of partial discharges,existing partial discharge monitoring methods based on single data source suffer from low information utilization and limited identification accuracy.To address these challenges,a refined identification method for partial discharge in power equipment based on acoustic-optical fusion imaging feature analysis is proposed.First,sliding feature extraction is performed on the collected discharge audio and acoustic images to form a feature matrix of acoustic-optical fusion.The feature matrix is then embedded into a multivariate time series,and a gate controlled dual-axis encoding model is used to extract information,allocate weights,and recognize features in parallel along both the time and feature dimensions.Finally,the probability of the recognized feature vector belonging to each discharge category is calculated to achieve high-precision identification.Results show that the proposed method can achieve accurate identification of multiple types of discharge with an accuracy of up to 98.32％,outperforming identification methods based on single-source features.关键词
局部放电/声光融合成像/多元特征解析/时间序列/模式识别Key words
partial discharge/acoustic-optical fusion imaging/multivariate feature analysis/time series/pattern recognition引用本文复制引用
马富齐,穆睿昕,贾嵘,王波,赵宇航,马恒瑞..基于声光融合成像特征解析的电力设备局部放电精细识别方法研究[J].电力系统保护与控制,2025,53(11):51-62,12.基金项目
This work is supported by the National Science Basic Research Program of Shaanxi Province(No.2024JC-YBQN-0433).陕西省自然科学基础研究计划(2024JC-YBQN-0433) （No.2024JC-YBQN-0433）
国家科技部高端外国专家引进计划(G2023041010L) （G2023041010L）
