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Appl. Sci. 2017, 7(4), 414; doi:10.3390/app7040414

Research on the Blind Source Separation Method Based on Regenerated Phase-Shifted Sinusoid-Assisted EMD and Its Application in Diagnosing Rolling-Bearing Faults

1,2,3
,
1,2
,
1,2,* , 4
and
1,2
1
Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan 430081, China
2
Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
3
The State Key Laboratory of Refractories and Metallurgy, Wuhan University of Science and Technology, Wuhan 430081, China
4
Zhejiang Institute of Mechanical & Electrical Engineering, Hangzhou 310053, China
*
Author to whom correspondence should be addressed.
Academic Editors: Richard Yong Qing Fu and David He
Received: 7 January 2017 / Revised: 1 April 2017 / Accepted: 17 April 2017 / Published: 19 April 2017
(This article belongs to the Special Issue Structural Health Monitoring (SHM) of Civil Structures)
View Full-Text   |   Download PDF [5574 KB, uploaded 19 April 2017]   |  

Abstract

To improve the performance of single-channel, multi-fault blind source separation (BSS), a novel method based on regenerated phase-shifted sinusoid-assisted empirical mode decomposition (RPSEMD) is proposed in this paper. The RPSEMD method is used to decompose the original single-channel vibration signal into several intrinsic mode functions (IMFs), with the obtained IMFs and original signal together forming a new observed signal for the dimensional lifting. Therefore, an undetermined problem is transformed into a positive definite problem. Compared with the existing EMD method and its improved version, the proposed RPSEMD method performs better in solving the mode mixing problem (MMP) by employing sinusoid-assisted technology. Meanwhile, it can also reduce the computational load and reconstruction errors. The number of source signals is estimated by adopting singular value decomposition (SVD) and Bayes information criterion (BIC). Simulation analysis has demonstrated the superiority of this method being applied in multi-fault BSS. Furthermore, its effectiveness in identifying the multi-fault features of rolling-bearing has been also verified based on a test rig. View Full-Text
Keywords: blind source separation; regenerated phase-shifted sinusoid-assisted EMD; fault diagnosis blind source separation; regenerated phase-shifted sinusoid-assisted EMD; fault diagnosis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Yi, C.; Lv, Y.; Xiao, H.; You, G.; Dang, Z. Research on the Blind Source Separation Method Based on Regenerated Phase-Shifted Sinusoid-Assisted EMD and Its Application in Diagnosing Rolling-Bearing Faults. Appl. Sci. 2017, 7, 414.

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