Identification of faults through wavelet transform vis-à-vis fast Fourier transform of noisy vibration signals emanated from defective rolling element bearings

doi:10.1007/s11465-014-0298-6

Front. Mech. Eng.

2014, Vol. 9

Issue (2) : 130-141 https://doi.org/10.1007/s11465-014-0298-6

RESEARCH ARTICLE

Identification of faults through wavelet transform vis-à-vis fast Fourier transform of noisy vibration signals emanated from defective rolling element bearings

Deepak PALIWAL(

), Achintya CHOUDHURY, T. GOVANDHAN

Department of Mechanical Engineering, Sir Padampat Singhania University, Udaipur 313601, Rajasthan, India

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Abstract

Fault diagnosis of rolling element bearings requires efficient signal processing techniques. For this purpose, the performances of envelope detection with fast Fourier transform (FFT) and continuous wavelet transform (CWT) of vibration signals produced from a bearing with defects on inner race and rolling element, have been examined at low signal to noise ratio. Both simulated and experimental signals from identical bearings have been considered for the purpose of analysis. The bearings have been modeled as spring-mass-dashpot systems and the simulated signals have been obtained considering transfer functions for the bearing systems subjected to impulsive loads due to the defects. Frequency B spline wavelets have been applied for CWT and a discussion on wavelet selection has been presented for better effectiveness. Results show that use of CWT with the proposed wavelets overcomes the short coming of FFT while processing a noisy vibration signals for defect detection of bearings.

Keywords Fault detection spline wavelet continuous wavelet transform fast Fourier transform

Corresponding Author(s): Deepak PALIWAL

Issue Date: 22 May 2014

Cite this article:

Deepak PALIWAL,Achintya CHOUDHURY,T. GOVANDHAN. Identification of faults through wavelet transform vis-à-vis fast Fourier transform of noisy vibration signals emanated from defective rolling element bearings[J]. Front. Mech. Eng., 2014, 9(2): 130-141.

URL:

https://academic.hep.com.cn/fme/EN/10.1007/s11465-014-0298-6
https://academic.hep.com.cn/fme/EN/Y2014/V9/I2/130

Fig.1 Spring mass damping dashpot of rolling element bearing

Fig.2 Control diagram of bearing system subjected to (a) inner race defect impulse force and (b) rolling element defect impulse force

Fig.3 Simulated impulse response train: considering inner race defect (a) without noise and (c) with noise; considering rolling element defect (b) without noise and (d) with noise

Tab.1 6205-2RS JEM SKF, deep groove ball bearing specifications

Tab.2 Characteristic defect frequencies of bearing at 1730?r/min i.e. shaft frequency (f_s = 28.83?Hz)

Tab.3 Stiffness/damping values adopted for simulation of defect induced impulse responses

Fig.4 Envelope signal of (a) inner race defect impulse response train and (b) rolling element defect impulse response

Fig.5 (a) FFT of inner race envelope signal without noise; FFT spectrum of envelope signal at (b) S/N 2.8730 db & (c) −1.8982 db; FFT of rolling element envelope signal (d) without noise & (e) at S/N −0.1609 db

Fig.6 (a) Overlapping of simulated inner race defect impulse response and frequency B spline wavelet fbsp500-105-89.98; (b) Wavelet and defect response decay representation

Fig.7 (a) Overlapping of simulated rolling element defect impulse response and frequency B spline wavelet fbsp500-105-89.88; (b) Wavelet and defect response decay representation

Fig.8 (a) Simulated impulses of inner race defect response; (b) CWT of signal (a) in 2D; (c) CWT of signal (a) in 3D; (d) Simulated signal of inner race defect at S/N −4.1167 db; (e) CWT of signal (d) in 3D; (f) Simulated signal of rolling element defect at S/N −4.3943 db; (g) CWT of signal (f) in 3D, considering 6205-2RS JEM SKF bearing rotating at 1730?r/min

Fig.9 FFT of inner race defective bearing envelope signal captured by (a) driver end accelerometer & (b) fan end accelerometer; (c) FFT of rolling element defective bearing envelope signal captured by driver end accelerometer at 1730?r/min

Fig.10 CWT representation of inner race defective bearing vibration signal captured by (a) driver end accelerometer & (b) fan end accelerometer; (c) CWT representation of rolling element defective bearing vibration signal captured by driver end accelerometer

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