Harmonic wavelet-based data filtering for enhanced machine defect identification

被引:74
作者
Yan, Ruqiang [1 ]
Gao, Robert X. [2 ]
机构
[1] Southeast Univ, Sch Instrument Sci & Engn, Nanjing 210096, Jiangsu, Peoples R China
[2] Univ Connecticut, Dept Mech Engn, Storrs, CT 06269 USA
基金
美国国家科学基金会;
关键词
VIBRATION; CLASSIFICATION; TRANSFORM; LOCALIZATION;
D O I
10.1016/j.jsv.2010.02.005
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
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. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3203 / 3217
页数:15
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