Harmonic wavelet-based data filtering for enhanced machine defect identification
Harmonic wavelet-based data filtering for enhanced machine defect identification
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DOI：
10.1016/j.jsv.2010.02.005
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发表时间：
2010-07
影响因子：
4.7
通讯作者：
Ruqiang Yan;R. Gao
中科院分区：
文献类型：
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作者：
Ruqiang Yan;R. Gao
提出了一种用于增强旋转机械系统故障识别的滤波器构造技术。在广义调和小波变换的基础上，通过选取不同的调和小波参数对，构造了一系列的子带小波系数。然后计算与每个子频带相关联的能量和熵。通过选取对应的子频带具有最大能量熵比的小波系数来获得滤波信号。对含有不同类型结构缺陷的滚动轴承进行的实验研究证实，开发的新技术能够实现高信噪比，有效地识别机器缺陷。
A filter construction technique is presented for enhanced defect identification in rotary machine systems. Based on the generalized harmonic wavelet transform, a series of sub-frequency band wavelet coefficients are constructed by choosing different harmonic wavelet parameter pairs. The energy and entropy associated with each sub-frequency band are then calculated. The filtered signal is obtained by choosing the wavelet coefficients whose corresponding sub-frequency band has the maximum energy-to-entropy ratio. Experimental studies using rolling bearings that contain different types of structural defects have confirmed that the developed new technique enables high signal-to-noise ratio for effective machine defect identification.