Bearing defect diagnosis based on harmonic wavelet transform and singular value ratio spectrum

Hou Zhefei, Wang Yunpeng, K. Yong
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Abstract

A novel signal processing algorithm was proposed here for vibration signal analysis in condition monitoring and health diagnosis of rolling bearings. Such technique required an envelope being extracted from vibration signal with Harmonic Wavelet Transform. The principal periodic component in the envelope was subsequently detected, enhanced and reconstructed with sweep frequency method based on singular value ratio (SVR) spectrum. Such signal processing approach was experimentally evaluated by using vibration signals measured on rolling element bearings that contained localized structural defects with proved validity and efficiency.
基于谐波小波变换和奇异值比谱的轴承缺陷诊断
针对滚动轴承状态监测和健康诊断中的振动信号分析,提出了一种新的信号处理算法。该技术要求对振动信号进行谐波小波变换提取包络。利用基于奇异值比(SVR)谱的扫描频率法对包络中的主周期分量进行检测、增强和重构。以含局部结构缺陷的滚动轴承振动信号为实验对象,验证了该信号处理方法的有效性和有效性。
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