Laplace and Morlet Wavelet Analysis for Gear Fault Diagnosis: A Comparative Study
Praneeth Chandran1, M. Lokesha2, M.C. Majumder3, K.P. Ramachandran4

1Mr. Praneeth Chandran, Vellore Institute of Technology, Vellore, (Tamil Nadu), India.
2Mr. M. Lokesha, Caledonian College of Engineering, Oman.
3Dr. M.C Majumder, Department of Mechanical Engineering, NIT, Durgapur (West Bengal), India.
4Dr. Ramachandran K.P, Caledonian College of Engineering, Oman.
Manuscript received on 11 June 2013 | Revised Manuscript received on 17 June 2013 | Manuscript Published on 30 June 2013 | PP: 31-35 | Volume-3 Issue-1, June 2013 | Retrieval Number: A0887063113/13©BEIESP
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Abstract: The machines need to be developed with high speed and light weight to acquire market in this present competitive world and maintenance of these machines become critical and important to ensure failure free operation. Gear drives form a major component of any industrial machine and detection of faults at incipient stage is very crucial in order to reduce maintenance downtime of machine before the major failure. Vibrations emitted from faulty gears are rather non stationary and non-periodic signals and hence it is difficult to detect the gear fault by conventional FFT analysis. Therefore an effective and sophisticated signal processing method using wavelet analysis has successfully being applied. This paper investigates the application of Laplace wavelet kurtosis for gear fault diagnosis. Also, this paper presents the optimisation of wavelet parameters to maximize the kurtosis parameter in order to render the wavelet coefficients sensitive to the generated fault signals. Further, this paper compares the use of Morlet and Laplace wavelet kurtosis for automated fault detection in gears for various fault stages and also compares the Laplace and Morlet wavelet kurtosis for varying working condition.
Keywords: Wavelet, Morlet Wavelet, Laplace Wavelet Kurtosis, Gear.

Scope of the Article: Design and Diagnosis