Gear fault detection under time-varying rotating speed via joint application of multiscale chirplet path pursuit and multiscale morphology analysis

Abstract

This article reports a new method for gear fault detection under time-varying rotating speed. This method is based on the chirplet path pursuit and multiscale morphology analysis. The instantaneous rotating speed is extracted from the gear vibration signal using the multiscale chirplet path pursuit algorithm. According to the extracted rotation speed, the gear vibration signal is resampled at constant angle increment and as such the nonstationary signal is converted into a stationary signal. The fault-induced impulsive features can then be extracted from the resampled signal via the multiscale morphology analysis, followed by the spectrum analysis to reveal the fault characteristic frequency. Because of the low correlations between the noise and chirplet functions, the rotational speed can be extracted effectively even when the signal-to-noise ratio of the vibration signal is relatively low. In addition, the noise effect can be further suppressed by averaging the results of morphology analyses of all the scales. Therefore, the proposed approach has a good antinoise ability and is suitable for gear fault detection under time-varying rotational speed. The performance of the method has been validated by both simulation and experimental data.

Keywords

Chirplet path pursuit order tracking multiscale morphology analysis gear fault detection variable shaft speed

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References

Ding

Zhu

. Diagnosis and its application in gear and gearbox. Beijing: Mechanical Industry, 2005.

Dalpiaz

Rivola

Rubini

. Effectiveness and sensitivity of vibration processing techniques for local fault detection in gears. Mech Syst Sig Process 2000; 14(3): 387–412.

Feldman

. Non-linear free vibration identification via the Hilbert transform. J Sound Vib 1997; 208(3): 475–489.

Fan

Zuo

. Gearbox fault detection using Hilbert and wavelet packet transform. Mech Syst Sig Process 2006; 20(4): 966–982.

Maragos

Kaiser

Quatieri

. On amplitude and frequency demodulation using energy operator. IEEE Trans Signal Process 1993; 41(4): 1532–1550.

Liang

Bozchalooi

. An energy operator approach to joint application of amplitude and frequency-demodulations for bearing fault detection. Mech Syst Sig Process 2010; 24(5): 1473–1494.

Zhang

Yang

. Multiscale morphology analysis and its application to fault diagnosis. Mech Syst Sig Process 2008; 22(3): 597–610.

. Hidden Markov model-based fault diagnostics method in speed-up and speed-down process for rotating machinery. Mech Syst Sig Process 2005; 19(2): 329–339.

Meltzer

Ivanov

. Non-stationary rotational speed—part 1: the time-frequency approach. Mech Syst Sig Process 2003; 17(5): 1033–1047.

10.

Meltzer

Dien

. Fault diagnosis in gears operating under non-stationary rotational speed using polar wavelet amplitude maps. Mech Syst Sig Process 2004; 18(5): 985–992.

11.

Kim

Parlos

. Model-based fault diagnosis of induction motors using non-stationary signal segmentation. Mech Syst Sig Process 2002; 16(2–3): 223–253.

12.

Antoni

. The spectral kurtosis: a useful tool for characterizing non-stationary signals. Mech Syst Sig Process 2006; 20(2): 282–307.

13.

Cempel

Tabaszewski

. Multidimensional condition monitoring of machines in non-stationary operation. Mech Syst Sig Process 2007; 21(3): 1233–1241.

14.

Sawalhi

Randall

Endo

. The enhancement of fault detection and diagnosis in rolling element bearings using minimum entropy deconvolution combined with spectral kurtosis. Mech Syst Sig Process 2007; 21(6): 2616–2633.

15.

Qin

Tang

. Order-tracking of rotating machinery based on instantaneous frequency estimation. Chin J Mech Eng 2003; 39(3): 32–36.

16.

Gao

Guo

Chi

. Order tracking based on robust peak search instantaneous frequency estimation. J Phys Conf Ser 2006; 48: 479–484.

17.

Candès

Charlton

Helgason

. Detecting highly oscillatory signals by chirplet path pursuit. Appl Comput Harmon Anal 2008; 24(1): 14–20.

18.

Candès

Charlton

Helgason

. Gravitational wave detection using multiscale chirplets. Classical Quantum Gravity 2008; 25(18): 1–12.

19.

Peng

Luo

. Sparse signal decomposition method based on multi-scale chirplet and its application to the fault diagnosis of gearboxes. Mech Syst Sig Process 2011; 25(2): 549–557.

20.

Chandre

Wiggins

Uzer

. Time–frequency analysis of chaotic systems. Physica D 2003; 181(3–4): 171–196.