高压电器2017，Vol.53Issue(11)：1-8,8.DOI:10.13296/j.1001-1609.hva.2017.11.001
基于复合评价指标的金属微粒声发射信号最优小波去噪及其特征提取
Optimal Wavelet Denoising and Feature Extraction of Acoustic Emission Signal Caused by the Metal Particles by Using Composite Evaluation Index
律方成 1张瑜 1董蒙 1李志兵 2颜湘莲 2孙继星 3刘宏宇1
作者信息
- 1. 华北电力大学,北京102206
- 2. 中国电力科学研究院,北京100192
- 3. 北京交通大学,北京100044
- 折叠
摘要
Abstract
Metal particles weaken the dielectric strength of DC GIL significantly.Acoustic emission signals caused by the impact between metal particles and grounding electrode can reflect the motion state of the metal particles.The acoustic emission signal often accompanied by noise in the process of the detection.This paper built a wavelet denoising composite evaluation index which is suitable for acoustic emission signals.By using that composite evaluation index,this paper came up with an optimal wavelet de-noising algorithm.It is shown that through the denoising of the signals obtained from experiment platform and the signals artificially added colored noise,the composite evaluation indexes proposed in this paper can evaluate the noise effect of acoustic emission signals better than that of traditional single evaluation indexes.The optimal wavelet de-noising algorithm based on this composite index can effectively denoising acoustic emission signals.Furthermore,based the de-noised acoustic emission signals,this paper extracted the energy characteristics of the signal and the velocity of metal particles,fitted the correlation between electric field intensity and the characteristics of the signal mentioned before.The results indicate that,with the increase of electrode electric field strength,particle velocity and signal energy trend to increase as a linear function.关键词
气体绝缘金属封闭输电线路(GIL)/复合评价指标/声发射信号/最优小波去噪/特征提取Key words
gas insulated line(GIL)/composite evaluation index/acoustic emission signals/optimal wavelet denoising/feature extraction引用本文复制引用
律方成,张瑜,董蒙,李志兵,颜湘莲,孙继星,刘宏宇..基于复合评价指标的金属微粒声发射信号最优小波去噪及其特征提取[J].高压电器,2017,53(11):1-8,8.
