自适应冗余提升小波降噪分析及其在轴承故障识别中的应用

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振动与冲击 ›› 2013, Vol. 32 ›› Issue (7) : 54-57.

论文

自适应冗余提升小波降噪分析及其在轴承故障识别中的应用

阳子婧，蔡力钢，高立新

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Adaptive Redundant Lifting Wavelet Denoising Analysis and Its Application in Bearing Fault Identification

Zijing Yang, Ligang Cai, Lixin Gao

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摘要

为有效识别机械设备中滚动轴承的微弱故障信息，本文提出一种自适应冗余提升小波降噪方法。根据待分解低频尺度系数所含的不同特征，应用范数准则来自适应地选取最匹配于该尺度系数特征的小波函数。同时，引入多孔算法，用以通过冗余性来保证逐层分解后各尺度系数和小波系数所含有的丰富的信息量。接下来，对各层小波系数采用变尺度阈值降噪算法，并对降噪后的系数进行重构及包络谱分析，进而提取滚动轴承的故障特征。应用上述方法分别对轴承实验台轴承混合故障信号和现场实际信号进行分析，均较好地实现了故障识别，验证了本文方法的有效性。

Abstract

In this paper, an adaptive redundant lifting wavelet denoising method is proposed to realize effective identification of weak fault information of roller bearing in mechanical equipments. According to the different features contained in scale coefficients that are to be decomposed, wavelets which can optimally match these features are adaptively selected based on the norm criteria. Meanwhile, algorithm is introduced here to guarantee sufficient information in each scale coefficients and wavelet coefficients after every decomposition. Then the variable scale threshold denoising algorithm is applied to process each wavelet coefficients, followed by reconstruction and envelope spectrum analysis to abstract fault features of roller bearing. Analytical results obtained by adopting the method presented above of both compound fault signal of experiment table and field practical signal show that, fault identification can be well realized and the method discussed in this paper is of effectiveness.
Key words: Adaptive; Redundant lifting wavelet; Denoising; Bearing ; Fault identification

导出引用

阳子婧;蔡力钢;高立新. 自适应冗余提升小波降噪分析及其在轴承故障识别中的应用[J]. 振动与冲击, 2013, 32(7): 54-57

Zijing Yang;Ligang Cai;Lixin Gao . Adaptive Redundant Lifting Wavelet Denoising Analysis and Its Application in Bearing Fault Identification[J]. Journal of Vibration and Shock, 2013, 32(7): 54-57