Discrete wavelet-based thresholding study on acoustic emission signals to detect bearing defect on a rotating machine

A five stage “Roots and Claw” dry vacuum pump is a typical kind of quasi-steady state high speed rotating machine. The research using the novel Acoustic Emission measurement and Wavelet technique aims to develop advanced detection methods for dry vacuum pumps to prevent pumps’ failure. In this paper, denoising problem of Acoustic Emission signal is studied by using Discrete Wavelet Transform thresholding methods. The Donoho-Johnstone threshold method and parameter method are studied and compared. The Birgé-Massart strategy outperforms other estimators in our case. The denoised Acoustic Emission signals enable detection of the defect and identification of the type of bearing defect. Care has to be taken on proper selecting wavelet basis to reduce the bias and error. The study shows us the Discrete Wavelet Transform-based thresholding method is suitable for Acoustic Emission signals to detect bearing defect of rotating machines.