Multiple random fault sources adaptive blind separation in situation of time-varying source signals and system

Cheng Wang1, Yanxia Hu2, Wei Zhan3, Jianying Wang4, Baokun Yang5, Yiwen Zhang6, Yewang Chen7

1, 2, 3, 4, 6, 7College of Computer Science and Technology, HuaQiao University, Xiamen, China

1State Key Laboratory for Strength and Vibration of Mechanical Structures, Xi’an Jiaotong University, Xi’an, China

5Beijing Aerospace Automatic Control Institute, Beijing, China

1Corresponding author

E-mail: 1wangcheng@hqu.edu.cn, 2847089912@qq.com, 3willalex@hqu.edu.cn, 41533353745@qq.com, 5pengkun19@126.com, 6zyw@hqu.edu.cn, 7ywchen@hqu.edu.cn

Received 11 September 2017; accepted 20 September 2017

DOI https://doi.org/10.21595/vp.2017.19174

 

Abstract. In order to separate multiple random fault source signals adaptively only from mixed vibration measurement signals of mechanical system in the situation of time-varying source signals and mixture system, two adaptive blind identification and separation methods are proposed to solve this kind of problem. One is based on recursive least squares (RLS) algorithm and another is based on recursive EASI algorithm. The simulation results show that both of these methods can separate source signals from the mixed signal in the situation of time-varying source signals and mixture system very well.

Keywords: blind source separation, multiple random fault sources, time-varying, adaptive, recursive least squares algorithm, recursive EASI algorithm.

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Cite this article

Wang Cheng, Hu Yanxia, Zhan Wei, Wang Jianying, Yang Baokun, Zhang Yiwen, Chen Yewang Multiple random fault sources adaptive blind separation in situation of time‑varying source signals and system. Vibroengineering PROCEDIA, Vol. 14, 2017, p. 82‑86.

 

© JVE International Ltd. Vibroengineering PROCEDIA. Oct 2017, Vol. 14. ISSN 2345-0533