现代雷达2025，Vol.47Issue(5)：52-58,7.DOI:10.16592/j.cnki.1004-7859.20231019001
基于TasNet和NGCC的变压器局放声源定位
Transformer Partial Discharge Sound Plot Position Based on TasNet and NGCC
摘要
Abstract
Aimed at the problem of low localization accuracy and long delay of transformer partial discharge sound plot position,a transformer partial discharge sound plot positioning method based on time-domain audio separation network(TasNet)and neural gen-eralized cross-correlations(NGCC)is proposed in this paper.Firstly,the features of the audio sequences are identified and separa-ted through the mic-array and the TasNet network;then,the estimated time differences of arrival(TDOA)value corresponding to the partial discharge sound plot based on the convolutional neural network are obtained;finally,a positioning framework to calculate the location information of the partial discharge sound plot is built to achieve localization of transformer partial discharge sound plot.Ex-periments show that compared with the traditional method based on generalized cross-correlation function with phase transform(GCC-PHAT),the method proposed in this paper significantly improves the accuracy and efficiency of partial discharge sound plot position.关键词
局放声源定位/神经网络类的广义互相关/时域语音分离卷积网络/到达时间差Key words
partial discharge sound plot position/neural generalized cross-correlation(NGCC)/time-domain audio separation net-work(TasNet)/time differences of arrival(TDOA)分类
电子信息工程引用本文复制引用
刘扬,严天峰,郑礼,张卓..基于TasNet和NGCC的变压器局放声源定位[J].现代雷达,2025,47(5):52-58,7.基金项目
甘肃省科技重大专项资助项目(22ZD6GA041) （22ZD6GA041）
甘肃省拔尖人才资助项目(6660030102) （6660030102）
甘肃省重点人才资助项目(6660010201) （6660010201）
