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A Wavelet Decomposition Analysis of Vibration Signal for Bearing Fault Detection

Che Ku Eddy Nizwan, Che Ku Husin and S. A., Ong and Mohd Fadhlan, Mohd Yusof and Mohamad Zairi, Baharom (2013) A Wavelet Decomposition Analysis of Vibration Signal for Bearing Fault Detection. In: International Conference on Mechanical Engineering Research (ICMER2013), 1-3 July 2013 , Bukit Gambang Resort City, Kuantan, Pahang, Malaysia. pp. 1-9.. (Unpublished)


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This paper presents the study of vibrational signal analysis for bearing fault detection using Discrete Wavelet Transform (DWT). In this study, the vibration data were acquired from three different type of bearing defect i.e. corroded, outer race defect and point defect. The experimental were carried out at three different speeds which are 10%, 50% and 90% of the maximum motor speed. The time domain vibration data measured from accelerometer was then transform into frequency domain using frequency analyzer in order to study the frequency characteristics of the signal. The DWT was utilized to decomposed signal at different frequency scale. Then, root mean square (RMS) for every decomposition level were calculated to detect the defect features in vibration signals by referring to the trend of vibrational energy retention at every decomposition. Based on the result, the defective bearings show the significant deviation in retaining RMS value after a few level of decomposition. The findings indicate that Wavelet decomposition analysis can be used to develop an effective bearing condition monitoring tool. This signal processing analysis is recommended to use in on-line monitoring while the machine is on operation.

Item Type: Conference or Workshop Item (Speech)
Uncontrolled Keywords: Condition monitoring; Bearing fault detection; Signal analysis; Wavelet transform
Subjects: T Technology > TJ Mechanical engineering and machinery
Faculty/Division: Faculty of Mechanical Engineering
Depositing User: fawaz
Date Deposited: 08 Apr 2014 04:31
Last Modified: 01 Mar 2018 08:00
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