Intelligent bearing fault signature extraction via iterative oscillatory behavior based signal decomposition (IOBSD)
作者：
Highlights：
• A method based on oscillatory behaviors is proposed for bearing fault detection.
• The IOBSD is developed for handling signals with multiple interferences.
• The strategies of Q-factor determination and tuning for TQWT are exploited.
• The proposed method can remove in-band interferences and noise.
• The proposed method requires neither prior signal knowledge nor prefiltering.
摘要
•A method based on oscillatory behaviors is proposed for bearing fault detection.•The IOBSD is developed for handling signals with multiple interferences.•The strategies of Q-factor determination and tuning for TQWT are exploited.•The proposed method can remove in-band interferences and noise.•The proposed method requires neither prior signal knowledge nor prefiltering.
论文关键词：Bearing fault diagnosis,Fault signature extraction,Oscillatory behavior based signal decomposition,Tunable Q-factor wavelet transform,Morphological component analysis
论文评审过程：Received 11 November 2014, Revised 22 September 2015, Accepted 23 September 2015, Available online 3 October 2015, Version of Record 16 October 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.09.039
