Research of Rolling Bearing Fault Feature Extraction Based on EMD and Choi-Williams

Abstract:

Aiming at rolling bearing fault signal of the non stationary feature, Apply a new method to the rolling bearing vibration signal of feature extraction, which is combined the Empirical Mode Decomposition (EMD) and the Choi-Williams distribution. Firstly, original signals were decomposed into a series of intrinsic mode functions (IMF) of different scales. To the decomposed each IMF component for Choi-Williams time-frequency analysis, Then take the linear superposition, finally obtained the rolling bearing vibration signal of Choi-Williams distribution. After the analyses of the rolling bearing inner ring, outer ring and rolling element fault signal ,the results show that this method can effectively suppress the frequency aliasing and interference caused by cross terms. And be able to accurately extract the fault frequency of the bearing inner ring, outer ring and rolling element, lay the foundation for the subsequent rolling bearing state recognition.

• Periodical: Advanced Materials Research (Volumes 694-697)
• Pages: 1377-1381
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.694-697.1377
• Online since: May 2013
• Authors: Xing Chun Wei, Yu Lin Tang, Tao Chen
• Keywords: Empirical Mode Decomposition (EMD), Exponential Distribution, Fault Diagnosis, Feature Extraction

References

[1] N. E. Huang, Z. Shen, S. R. Long, M. L.Wu, H. H. Shih, Q. Zheng, N. C.Yen, C. C. Tung, and H. H. Liu, The empirical mode decomposition and Hilbert spectrum for nonlinear and nonstationary time series analysis[J],Proc. R. Soc. London A, vol. 454, p.903–995, 1998.

DOI: 10.1098/rspa.1998.0193

[2] Cohen L .Time-frequency distribution a review[J]. Proceedings of the IEEE,1989, 77(7):941-981

[3] Huguang,shu. Modern Signal Processing Guid[M]. Beijing:Tsinghua University Press,2004.

[4] Yude Jie,Chengjun sheng,Yang Yu.Mechanical fault diaynosis method of Hibert-Huang transformation[M].Beijing:Social Sciences Publishing House.2006.

[5] H.Li,H.Q. Zheng and L.W. Tang. Hilbert-Huang Transform and its Application in Gear Faults Diagnosis[J]. Key Engineering Materials Vols. 291-292(2005):655-660.

DOI: 10.4028/www.scientific.net/kem.291-292.655

[6] Wang W J ,Chen J ,Wu X K .The application of some non-linear methods in rotating machinery fault diagnosis[J]. Mechanical Systems and Signal Processing, 2001, 15(4):697-705.

DOI: 10.1006/mssp.2000.1316

[7] Gravier B .M .,Pelstring J. A . An assessment of the applications of the Hilbert spectrum to the fatigue analysis of marine risers[J].Proceedings of the International Offshore and Polar Engineering Conference, 2001(2):268-275.

[8] Information on http://csegroups.case.edu/bearingdatacenter/pages/download-data-file