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Bearing Health Analysis using Time - Frequency Plot and Statistical Analysis

Author(s):

Prakash Tiwari , Barkatullah University Institute of Technology,Bhopal,MP; Dr. Rohit Rajvaidya, Barkatullah University Institute of Technology,Bhopal,MP

Keywords:

vibration analysis, critical frequencies, condition monitoring, wavelet transform, bearing fault

Abstract

Rolling element bearings are one of the most widely used elements in machines and their failure one of the most frequent reasons for machine breakdown. However any bearing defect (e.g. cracks, notch) occurring deteriorate the performance of the machine. Detection of the defect at its incipient stage and alerting/maintaining the user before it converts into a catastrophic failure is the aims of vibration monitoring technique. The vibration signals generated by faults in them have been widely studied and very powerful diagnostic techniques for observing bearing under a high rpm operating conditions. In the present research work vibration analyses have been focused to detect bearing fault at the early stage. To accomplish above tasks a bearing test rig, consisting of shaft-bearing in conjunction to a gear box and brake drum is used to demonstrate the effectiveness of vibration analysis real time data related to bearing vibrations. Afterwards a bearing with a crack is also examined for the fault detection. A faulty bearing vibration signal is acquired from the test rig; thereafter the fast Fourier transform is plotted to show the critical frequencies, bearing characteristics frequency and its harmonics for the online condition monitoring of the system. Post processing analysis is done for the time domain signal using the statistical parameters and scalogram showing the energy levels of impulses present in the signal is plotted as result. Both healthy & faulty signal are analyzed using wavelet transform to identify the fault in the bearing.

Other Details

Paper ID: IJSRDV3I40617
Published in: Volume : 3, Issue : 4
Publication Date: 01/07/2015
Page(s): 946-954

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