An Investigation of Tooth Wear Diagnosis of Gear Based on Process Systems Modeling

Feng Li Wang; Hui Xing

doi:10.4028/www.scientific.net/AMR.549.834

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 549An Investigation of Tooth Wear Diagnosis of Gear...

An Investigation of Tooth Wear Diagnosis of Gear Based on Process Systems Modeling

Abstract:

Targeting the advantages of local wave analysis(LWA) and the characteristics of gear fault vibration signals, LWA is introduced into gear fault diagnosis. The concept of the instantaneous energy in time- frequency analysis, based on local wave time-frequency spectrum, was used to measure the energy distribution of the signal in time-frequency domain. Furthermore, when tooth wear occurs in gear, the energy of the gear vibration signal would change correspondingly, whilst local wave time-frequency spectrum can exactly provide the instantaneous energy distribution of the signal with the change of the time and frequency. Thus, the fault information of the gear vibration signal can be extracted effectively from the local wave time-frequency spectrum. The analysis results from the experimental signals show that local wave time-frequency analysis could extract the characteristics information of the gear fault vibration signal effectively.

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Periodical:

Advanced Materials Research (Volume 549)

Pages:

834-838

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.549.834

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Online since:

July 2012

Authors:

Feng Li Wang, Hui Xing

Keywords:

Gear, Hilbert Transform, Local Wave Analysis, Systems Modeling, Tooth Wear

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References

[1] W. J. Wang: Journal of Sound and Vibration, vol. 192(1996, p.27.

Google Scholar

[2] G T Zheng, P D McFadden: Journal of Vibration and Acoustics, vol. 121(1999) , p.328.

Google Scholar

[3] J. Lin, M.J. Zuo: Mechanical Systems and Signal Processing, vol. 17(2003), p.1259.

Google Scholar

[4] F. L. Wang: Study on nonlinear dynamic characteristics and application for rotor system based on local wave method(Ph.D. dissertation, Dalian: Dalian University of Technology, 2003).

Google Scholar

[5] 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: Proceedings of the Royal Society of London, Series A454 (1998), p.903.

Google Scholar