Vibration Signal Analysis and Fault Diagnosis of Gears Based on Hilbert Marginal Spectrum

Abstract:

Hilbert-Huang transform is a new method of signal processing, which is very suitable for dealing with nonlinear and non-stationary signal. In this article, a gear fault diagnosis method based on Hilbert marginal spectrum is proposed in view of the non-stationary characteristics of gear vibration signal. First the original vibration signal is decomposed into several intrinsic mode functions (IMF) of different characteristic time scale smoothly by means of empirical mode decomposition (EMD) method. Then the Hilbert-Huang transform is carried out for IMF and the Hilbert marginal spectrum under different operating conditions are obtained. Gear faults can be judged through the analysis of the marginal spectrum. The experimental results show that this method can effectively diagnose the gear faults.

• Periodical: Advanced Materials Research (Volume 909)
• Pages: 121-126
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.909.121
• Online since: March 2014
• Authors: Jiang Ping Wang*, Jin Cui
• Keywords: Fault Diagnosis, Gear, Hilbert-Huang Transform, Marginal Spectrum, Vibration Signal

References

[1] Yu Hongying, Yan Hongwei, Pan Hongxia: Gear vibration signal analysis and its application to fault diagnosis. Journal of Vibration, Measurement &Diagnosis Vo l. 25 (2)(2005), pp.109-114.

[2] G. Meltzera, Nguyen Phong Dien: Fault diagnosis in gears operating under non-stationary rotational speed using polar wavelet amplitude maps, Mechanical Systems and Signal Processing 18 (2004), p.985–992.

DOI: 10.1016/j.ymssp.2004.01.009

[3] Li Fang, Li Yourong, Wang Zhigang: Harmonic wavelet spectrum plot with applications in gear fault diagnosis, Journal of Vibration and Shock, Vol. 26(3)( 2007), pp.128-132.

[4] N. E. Huang, Z. Shen, S. R. Long et al: The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceeding of Royal Society. London A, 454(1998), pp.903-995.

DOI: 10.1098/rspa.1998.0193

[5] Zhipeng Feng, Ming J. Zuo: Rujiang Hao et al: Ensemble Empirical Mode decomposition based Teager energy spectrum for bearing fault diagnosis. Journal of Vibration and Acoustics, JUNE Vol. 135 / 031013(2013), pp.1-21.

DOI: 10.1115/1.4023814

[6] Rodolfo T. Gonçalves, Guilherme R. Franzini, Guilherme F. Rosetti et al: Analysis methodology for vortex-induced motion (VIM) of a monocolumn platform applying the Hilbert–Huang transform method. Journal of Offshore Mechanics and Arctic Engineering, FEBRUARY, Vol. 134 / 011103(2012).

DOI: 10.1115/1.4003493

[7] Dejie Yu, Junsheng Cheng, Yu Yang, Application of EMD method and Hilbert spectrum to the fault diagnosis of roller bearings, Mechanical Systems and Signal Processing, 19 (2005), p.259–270.

DOI: 10.1016/s0888-3270(03)00099-2