电气技术  2017, Vol. 18 Issue (5): 30-33    DOI:
研究与开发 |
基于时域特征和小波分析的故障行波特征识别方法
李文国, 马秉宇
咸亨国际(杭州)电气制造有限公司,杭州 310022
The Method of Fault Traveling Wave Feature Recognition based on Time-Domain Characteristics and Wavelet Analysis
Li Wenguo, Ma Bingyu
Xianheng International (Hangzhou) Electric Infrastructure Co., Ltd, Hangzhou 310022
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摘要 随着电力电缆的应用越来越广泛,电力部门对突发的电缆故障定位精度和时效要求也越来越高。故障行波的特征识别是故障定位的关键环节。本文提出了基于时域特征和小波分析相结合的故障行波特征提取方法,先通过自适应阈值法对采集的原始信号进行预处理,滤除噪声后再结合微分和小波分析算法来提取行波中相邻回波的起始特征,最后计算出故障距离。经过实验验证,该方法提高了电缆故障定位的准确度,具有一定的实际应用价值。
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李文国
马秉宇
关键词 电力电缆故障行波时域特征小波分析    
Abstract:With the application of power cable becoming more and more widespread, the power sector is increasing the demands for accuracy and timeliness of cable fault location. Feature recognition of fault traveling wave is the key to fault location. This paper presents a feature extraction method of fault traveling wave based on combination of time-domain characteristics and wavelet analysis, which firstly filters noise of the original signal using adaptive threshold method, then applies differential and wavelet analysis algorithms to extracting the characteristics of starting point of two adjacent reflection waves, finally calculates the fault distance. Experimental results show that this method improves the accuracy of cable fault location, which has a certain practical application value.
Key wordspower cable    fault traveling wave    time-domain characteristics    wavelet analysis   
     出版日期: 2017-05-23
作者简介: 李文国(1982-),男,浙江省瑞安市人,硕士,工程师,主要从事电力电缆故障诊断和定位技术的研究工作。
引用本文:   
李文国, 马秉宇. 基于时域特征和小波分析的故障行波特征识别方法[J]. 电气技术, 2017, 18(5): 30-33. Li Wenguo, Ma Bingyu. The Method of Fault Traveling Wave Feature Recognition based on Time-Domain Characteristics and Wavelet Analysis. Electrical Engineering, 2017, 18(5): 30-33.
链接本文:  
https://dqjs.cesmedia.cn/CN/Y2017/V18/I5/30