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Induction Motor Bearing Fault Detection Using Wavelet-Based Envelope Analysis

机译:基于小波包络分析的异步电动机轴承故障检测

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This paper proposes a new signal processing approach based on the fusion of the wavelet transform and envelope spectrum to extract features of defects in a number of induction motor bearing conditions. The bearing conditions considered are a normal bearing and bearings with outer and inner race faults. This approach provides one solution to overcome the shortcomings of the traditional envelope analysis in finding the most suitable resonant frequency band for demodulation. Experiment results show that the proposed approach is capable of completely extracting the characteristic frequencies related to the defects in rolling element bearings.
机译:本文提出了一种基于小波变换和包络谱融合的信号处理新方法,以提取多种感应电动机轴承条件下的缺陷特征。所考虑的轴承条件是普通轴承以及具有内外圈故障的轴承。这种方法提供了一种解决方案,可以克服传统包络分析在寻找最合适的谐振频段进行解调方面的缺点。实验结果表明,该方法能够完全提取与滚动轴承缺陷有关的特征频率。

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