Blind Separation Method for Gearbox Mixed Fault Signals

Yan Bin Lei; Zhi Gang Chen; Hai Ou Liu

doi:10.4028/www.scientific.net/AMM.86.180

Paper Titles

Analysis of Static Load Sharing in Star Gearing
p.162

Active Gear Pair Vibration Control Based on Filtered-X RLS Algorithm
p.166

Preload Design of Bearings in Helicopter Transmission System
p.170

Dynamics Study of a Dynamic Balancing Linkage with Small Fluctuations in Load
p.176

Blind Separation Method for Gearbox Mixed Fault Signals
p.180

Analysis on Thermo-Mechanical Coupling Contact Stress of Cycloid Ball Planetary Drive
p.184

Computational Tooth Root Stress Analysis of Crossed Beveloid Gears with Small Shaft Angle
p.188

Research on Relationship between Modulus and Tooth Number of Transmitting Gear and Vibration Noise
p.192

Load-Excursion Failure Analysis of the Gearbox’s Input Pinion
p.196

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 86Blind Separation Method for Gearbox Mixed Fault...

Blind Separation Method for Gearbox Mixed Fault Signals

Abstract:

A new blind source separation (BSS) algorithm used for separating mixed gearbox signals is proposed in this paper. Firstly, whiten the observed signals, and then diagonalize the second- and higher-order cumulant matrix to get an orthogonal separation matrix. The feasibility of the algorithm is validated through separating the mechanical simulation signals and the gearbox vibration signals. The algorithm can successfully identified the failure source of the gearbox and provides a new method to a gearbox fault.

You might also be interested in these eBooks

Advances in Power Transmission Science and Technology

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 86)

Pages:

180-183

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.86.180

Citation:

Cite this paper

Online since:

August 2011

Authors:

Yan Bin Lei, Zhi Gang Chen, Hai Ou Liu

Keywords:

Blind Source Separation (BSS), Fault Diagnosis, Gearbox, Vibration Signal

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] K. Ding, X.Y. Zhu and Y.H. Chen: Journal of Vibration and Shock, Vol. 3(2001), p.7.

Google Scholar

[2] L.S. Qu and Z.J. He: Machinery Fault Diagnosis (Shanghai Scientific & Technical Publishers, China 1986).

Google Scholar

[3] W.D. Jiao: Research on Method for Fault Diagnosis of Rotating Machines Based on Independent Component Analysis. Doctor thesis (2003). Zhejiang University.

Google Scholar

[4] Gelle G, Colas M. Blind source separation: A new pre-processing tool for rotating machines monitoring. IEEE Transactions on Instrumentation and Measurement, Vol. 3 (2003), p.790.

DOI: 10.1109/tim.2003.814356

Google Scholar

[5] Y.L. Sun, W.H. Luo and H. Li: Extract Signals of Power Line Communication by a Novel Method Based on EMD and ICA. Proceedings of the CSEE. Vol. 16 (2007), p.109.

Google Scholar

[6] S.M. Li and T. Yang: Journal of Transducer and Technology. Vol. 4 (2005), p.1.

Google Scholar

[7] Y.B. Lei, S.M. Li and Q.Q. Hao: China Mechanical Engineering, Vol. 7(2010), p.35.

Google Scholar

[8] T. Blaschke: Independent component anlysis and slow feature analysis: relations and combination. (Humboldt-Universität zu, Berlin 2004).

Google Scholar

[9] T. Blaschke: An Improved Cumulant Based Method for Independent Component Analysis. Proceeding of International Conference on Artificial Neural Networks, ICANN'02, p.1087.

DOI: 10.1007/3-540-46084-5_176

Google Scholar