Article: Fault diagnosis of high-speed rolling element bearings using wavelet packet transform Journal: International Journal of Signal and Imaging Systems Engineering (IJSISE) 2015 Vol.8 No.6 pp.390 - 401 Abstract: The time-frequency analysis techniques like Continuous Wavelet Transform (CWT), Discrete Wavelet Transform (DWT) and wavelet packet analysis have been compared to detect and diagnose faults in rotor bearing system. Discrete Wavelet Transform (DWT) provides flexible time frequency resolution which suffers from a relatively low resolution in the high-frequency region. This deficiency leads to difficulty in differentiating high-frequency transient components. WPT based signal decomposition process up to n-level produces a total of 2n sub-bands, with each sub-band covering 1/2n of the signal frequency spectrum. WPT based global threshold criterion is applying before denoising of detail information. This denoised signal is then auto correlate with original signal and energy spectrum is generated for diagnosis of bearing fault. The enhanced signal decomposition capability makes WPT an attractive tool for detecting and differentiating transient elements with high-frequency characteristics and helping in the minimisation of interventions by the end user. Inderscience Publishers - linking academia, business and industry through research

Title: Fault diagnosis of high-speed rolling element bearings using wavelet packet transform

Authors: Divyang H. Pandya; Sanjay H. Upadhyay; Suraj P. Harsha

Addresses: Vibration & Noise Control Lab., Mechanical & Industrial Engineering Department, Indian Institute of Technology, Roorkee, Roorkee 247 667, Uttarakhand, India ' Vibration & Noise Control Lab., Mechanical & Industrial Engineering Department, Indian Institute of Technology, Roorkee, Roorkee 247 667, Uttarakhand, India ' Vibration & Noise Control Lab., Mechanical & Industrial Engineering Department, Indian Institute of Technology, Roorkee, Roorkee 247 667, Uttarakhand, India

Abstract: The time-frequency analysis techniques like Continuous Wavelet Transform (CWT), Discrete Wavelet Transform (DWT) and wavelet packet analysis have been compared to detect and diagnose faults in rotor bearing system. Discrete Wavelet Transform (DWT) provides flexible time frequency resolution which suffers from a relatively low resolution in the high-frequency region. This deficiency leads to difficulty in differentiating high-frequency transient components. WPT based signal decomposition process up to n-level produces a total of 2ⁿ sub-bands, with each sub-band covering 1/2ⁿ of the signal frequency spectrum. WPT based global threshold criterion is applying before denoising of detail information. This denoised signal is then auto correlate with original signal and energy spectrum is generated for diagnosis of bearing fault. The enhanced signal decomposition capability makes WPT an attractive tool for detecting and differentiating transient elements with high-frequency characteristics and helping in the minimisation of interventions by the end user.

Keywords: fault diagnosis; wavelet transforms; CWT; WPT; transient vibration signals; high-speed bearings; rolling element bearings; wavelet packet transform; continuous wavelet transform; rotor bearings; signal denoising; bearing faults.

DOI: 10.1504/IJSISE.2015.072922

International Journal of Signal and Imaging Systems Engineering, 2015 Vol.8 No.6, pp.390 - 401

Accepted: 13 Feb 2014
Published online: 08 Nov 2015 *

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Title: Fault diagnosis of high-speed rolling element bearings using wavelet packet transform

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