电工技术2024,Issue(23) :261-264,269.DOI:10.19768/j.cnki.dgjs.2024.23.063

利用小波窗口深入挖掘发电机故障异音特征量

Deep Mining of Characteristic Variables of Abnormal Sound of Faulty Generators Using Wavelet Window

赵冠霖 张强 杨露 赖奕帆 郭玉鑫
电工技术2024,Issue(23) :261-264,269.DOI:10.19768/j.cnki.dgjs.2024.23.063

利用小波窗口深入挖掘发电机故障异音特征量

Deep Mining of Characteristic Variables of Abnormal Sound of Faulty Generators Using Wavelet Window

赵冠霖 1张强 1杨露 1赖奕帆 1郭玉鑫1
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作者信息

  • 1. 新疆大学电气工程学院,新疆 乌鲁木齐 830046
  • 折叠

摘要

为了实现对矿山备用电厂同步电机运行状态的检测,给出了一种能够判断同步电机运行状态的方法.根据电机不同运行状态下产生声音信号的不同,利用 MATLAB强大的编程功能对同步电机音频信号进行滤波,并利用小波分析确定信号的参数特征,最后通过比对所得参数确定同步电机所处的运行状态.实验表明,MATLAB分析得到的常态和次暂态运行的同步电机声音参数差异较大,所提出的方法能够较好地判断同步电机所处的运行状态,便于实现对同步电机更好的控制,具有潜在实用价值.

Abstract

In order to detect operational status of synchronous motors in mines'auxiliary power plants,a method to deter-mine operational status of synchronous motors was proposed and studied.According to the different sound signals genera-ted by the motor under different status,the MATLAB powerful programming function was used to filter the sound sig-nals.Then the parameter characteristics of sound signals were obtained using wavelet analysis,and finally the motor oper-ation status was determined by comparing the obtained parameters.It was concluded from the experiment that the use of MATLAB analysis could obtain synchronous motor sound parameters with large difference between normal status and sub-normal status.The proposed method thereby can facilitate accurate determination of motor operational status and real-ization of better control of synchronous motors,exhibiting potential practical applicability.

关键词

同步电机/MATLAB/声音信号/小波分析

Key words

synchronous motor/MATLAB/sound signal/wavelet analysis

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出版年

2024
电工技术
重庆西南信息有限公司(原科技部西南信息中心)

电工技术

影响因子:0.177
ISSN:1002-1388
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