https://escholarship.org/content/qt4h56k1ch/qt4h56k1ch.pdf

Advanced monitoring of machining operations

Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography

Wavelet transform based on inner product in fault diagnosis of rotating machinery: A review

A method is proposed for the analysis of vibration signals resulting from bearings with localized defects using the wavelet packet transform (WPT) as a systematic tool. A time–frequency decomposition of vibration signals is provided and the components carrying the important diagnostic information are selected for further processing. The proposed method is designed in such a way that it can exploit the underlying physical concepts of the modulation mechanism, present in the vibration response of faulty bearings. The flexibility of the WPT and the systematic parameter selection criteria, help in the minimization of interventions by the end user. The method is evaluated using simulated and experimental signals.

Rolling element bearing fault diagnosis using wavelet packets

This paper reviews the state-of-the-art of wavelet analysis for tool condition monitoring (TCM). Wavelet analysis has been the most important non-stationary signal processing tool today, and popular in machining sensor signal analysis. Based on the nature of monitored signals, wavelet approaches are introduced and the superiorities of wavelet analysis to Fourier methods are discussed for TCM. According to the multiresolution, sparsity and localization properties of wavelet transform, literatures are reviewed in five categories in TCM: time–frequency analysis of machining signal, signal denoising, feature extraction, singularity analysis for tool state estimation, and density estimation for tool wear classification. This review provides a comprehensive survey of the current work on wavelet approaches to TCM and also proposes two new prospects for future studies in this area.

Ya Wu

Papers

Feature extraction and assessment using wavelet packets for monitoring of machining processes