噪声与振动控制2019，Vol.39Issue(3)：187-192,6.DOI:10.3969/j.issn.1006-1355.2019.03.036
基于声音信号的托辊故障诊断方法
Fault Diagnosis Method of Rollers based on Sound Signals
郝洪涛 1倪凡凡 2丁文捷1
作者信息
- 1. 宁夏大学 机械工程学院,银川 750021
- 2. 宁夏智能装备CAE重点实验室,银川 750021
- 折叠
摘要
Abstract
In order to realize the detection of the remote belt conveyor rollers, a set of fault diagnosis method was developed based on sound signals. A fusion scheme based on a variety of analytic methods was proposed according to the roller bearing characteristics of the long-distance belt conveyor. The scheme incorporated several detection methods such as time domain detection, FFT peak detection, power spectral density detection, wavelet packet decomposition, reconstruction and Hilbert envelope analysis, and empirical mode decomposition (EMD). It can realized acquired data display, waveform analysis and fault diagnosis. Among these detection methods, the roller failure can be preliminary judged by the time domain detection, FFT peak detection and power spectrum detection. The failure section of the belt conveyor rollers can be forecasted by EMD. The method combining wavelet packet decomposition and reconstruction with Hilbert envelope analysis can further extract the failure frequency of the roller bearing. With this method the location of the failed bearing can be determined. Finally, the experiment verified the effectiveness of this fault diagnosis method for rollers based on sound signal.关键词
声学/声音信号/托辊轴承/故障诊断/经验模态分解/小波包Key words
acoustics/ sound signal/ roller bearing/ fault diagnosis/ empirical mode decomposition/ wavelet packet分类
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郝洪涛,倪凡凡,丁文捷..基于声音信号的托辊故障诊断方法[J].噪声与振动控制,2019,39(3):187-192,6.
