Gear Pitting Corrosion Fault Diagnosis Based on Local Mean Decomposition

Article Preview

Abstract:

The local mean decomposition (LMD), a new adaptive time-frequency analysis method, is the research focus in the fault diagnosis field in recent years. In this paper, the LMD’s characteristics are obtained by processing multi-component frequency and amplitude modulation signal, which are usually used to describe the gear pitting corrosion fault signals. Base on the simulation analysis, LMD is presented to deal with the vibration signals of gear pitting corrosion fault, comparing with traditional method. The results show that the gear pitting corrosion defect can be diagnosed by LMD effectively, and LMD can eliminate the false composition effect, thus improving the accuracy of gear fault diagnosis.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 562-564)

Pages:

812-815

Citation:

Online since:

August 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Bi Guo, Chen Jin, Condition monitoring technology for gear vibration based on spectral correlation, Journal of Vibration and Shock, (2009), p.17 (in Chinese).

Google Scholar

[2] N. Saravanan , V.N.S. Kumar Siddabattuni, K.I. Ramachandran. A multidimensional hybrid intelligent method for gear fault diagnosis, Expert Systems with Applications,Vol. 37 (2010), p.1419.

DOI: 10.1016/j.eswa.2009.06.060

Google Scholar

[3] Yanxue Wang, Zhengjia He, Yanyang Zi. A demodulation method based on improved local mean decomposition and its application in rub-impact fault diagnosis. Measurement Science and Technology, Vol. 45 (2012), P. 561.

DOI: 10.1088/0957-0233/20/2/025704

Google Scholar

[4] Hui Li, Yuping Zhang, Haiqi Zheng. Application of Hermitian wavelet to crack fault detection in gearbox, Mechanical Systems and Signal Processing,Vol. 25 (2011), P. 1353.

DOI: 10.1016/j.ymssp.2010.11.008

Google Scholar

[5] Junsheng Cheng, Dejie Yu, Jiashi Tang, Yu Yang. Application of frequency family separation method based upon EMD and local Hilbert energy spectrum method to gear fault diagnosis, Mechanism and Machine Theory, Vol. 43 (2008) P. 712.

DOI: 10.1016/j.mechmachtheory.2007.05.007

Google Scholar

[6] Jonathan S Smith. The local mean decomposition and its application to EEG perception date, Vol. 2 (2005), p.443.

Google Scholar

[7] Junsheng Cheng, Yi Yang, Yu Yang. A rotating machinery fault diagnosis method based on local mean decomposition, Digital Signal Processing (2011), doi: 10. 1016/j. dsp. 2011. 09. 008.

DOI: 10.1016/j.dsp.2011.09.008

Google Scholar

[8] http: /web1. ulb. ac. be/polytech/laborulb.

Google Scholar