Rolling element bearing fault detection using acoustic emission signal analyzed by envelope analysis with discrete wavelet transform
Acoustic Emission (AE) what is a non-destructive testing technique is widely used for the early detection of faults in rotating machine in these days, because its sensitivity is higher than normal accelerometers and it can detect low energy vibration signals. The faults in rotating machines are generally occurred at bearing and/or gearboxes which are one of the principal parts of the machines. To detect the bearing fault, envelope analysis was studied and presented for several decade years. And the researches spoke that AE has a possibility of the application in condition monitoring system using envelope analysis for the rolling element bearing. And the peak ratio (PR) was developed for expression of the bearing condition in condition monitoring system using AE. The noise level is needed to reduce to get exact PR value because PR is calculated from total root mean square (RMS) and the harmonics of the defect frequencies. Therefore, in this paper, the discrete wavelet transform (DWT) was added in envelope analysis to reduce the noise level in AE signals. And then, the PR was calculated and compared with general envelope analysis result and the result of envelope analysis added DWT.
KeywordsAcoustic Emission Discrete Wavelet Transform Acoustic Emission Signal Peak Ratio Relevance Vector Machine
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