Early fault feature extraction of rolling bearing based on ICD and tunable Q-factor wavelet transform
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- 作者：Yongbo Lia ; b ; Xihui Liangb ; Minqiang Xua ; xumqhit@126.com" class="auth_mail" title="E-mail the corresponding author ; Wenhu Huanga
- 关键词：Signal decomposition ; Intrinsic characteristic-scale decomposition (ICD) ; Tunable Q-factor ; Wavelet transform (TQWT) ; Fault detection
- 刊名：Mechanical Systems and Signal Processing
- 出版年：2017
- 出版时间：1 March 2017
- 年：2017
- 卷：86
- 期：part_PA
- 页码：204-223
- 全文大小：3384 K
文摘
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CFR is propped to select the appropriate Q-factors for TQWT.
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The concept of CFR is defined.
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An early fault diagnosis method based on ICD and O-TQWT is developed.
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The proposed method is successfully applied to extract weak features of bearings at early fault stage in two run-to-failure experiments.