Cyclostationary Analysis Based Gear Fault Diagnosis

Abstract:

Gearbox vibrations acquired by sensors are random cyclostationary signals, which are a combination of periodic and random processes due to the machine’s rotation cycle and interaction with the real world. Since the spectral structure of a gear vibration signal is mainly characterized by the interaction between the meshing harmonics and their sidebands, the spectral correlation density (SCD) function has been applied to gear monitoring. This approach is capable of completely extracting the fault characteristic frequencies related to the defect. This gives a desirable ability to detect the singularity characteristic of a signal precisely. This technique permits both fault detection and identification of the damaged gear. The experimental results show that the proposed method based on cyclostationary analysis can effectively diagnose the faults of gear.

• Periodical: Advanced Materials Research (Volume 459)
• Pages: 190-194
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.459.190
• Online since: January 2012
• Authors: Zhen Tao Li, Hui Li
• Keywords: Cyclostationary Analysis, Fault Diagnosis, Gearbox, Signal Processing

References

[1] Hui Li, Yuping Zhang, Haiqi Zheng: Hilbert-Huang transform and marginal spectrum for detection and diagnosis of localized defects in roller bearings. Journal of Mechanical Science and Technology, Vol. 23, No. 2, (2009), pp.291-301.

DOI: 10.1007/s12206-008-1110-5

[2] J. Lin and L. Qu: Feature extraction based on Morlet wavelet and its application for mechanical fault diagnosis, Journal of Sound and Vibration, Vol. 234, No. 1, (2000), pp.135-148.

DOI: 10.1006/jsvi.2000.2864

[3] W.J. Wang: Wavelets for detecting mechanical faults with high sensitivity, Mechanical Systems and Signal Processing, Vol. 15, No. 4, (2001), pp.685-696.

DOI: 10.1006/mssp.2000.1369

[4] C. James Li and Jun Ma: Wavelet decomposition of vibration for detection of bearing-localized defects, NDT&E International, Vol. 30, (1997), pp.143-149.

DOI: 10.1016/s0963-8695(96)00052-7

[5] Hui Li, Haiqi Zheng, Liwei Tang: Bearing Fault Detection and Diagnosis Based on Order Tracking and Teager-Huang Transform, Journal of Mechanical Science and Technology, Vol. 24, No. 3, (2010), pp.811-822.

DOI: 10.1007/s12206-009-1211-9

[6] W.J. Wang and P.D. Mcfadden: Application of orthogonal wavelet to early gear damage detection, Mechanical Systems and Signal Processing, Vol. 9, (1995), pp.497-507.

DOI: 10.1006/mssp.1995.0038

[7] W.J. Staszewski, K. Worden and G.R. Tomlinson: The-frequency analysis in gearbox fault detection using the Wigner-Ville distribution and pattern recognition, Mechanical Systems and Signal Processing, Vol. 11, (1997), pp.673-692.

DOI: 10.1006/mssp.1997.0102

[8] C. Capdessus, M. Sidahmed, J.L. Lacoume: Cyclostationary process: application in gear faults diagnosis, Mechanical Systems and Signal Processing, Vol. 14, (2000), pp.371-385.

DOI: 10.1006/mssp.1999.1260

[9] A.C. Macormick, A.K. Nandi: Cyclostationarity in rotating machine vibrations, Mechanical Systems and Signal Processing, Vol. 12, (1998), pp.225-242.

DOI: 10.1006/mssp.1997.0148