Wavelet transform and multiresolution signal decomposition for machinery monitoring and diagnosis

摘要

Multiresolution signal decomposition based on wavelet transform or wavelet packet provides a set of decomposed signals in independent frequency bands, which contain most independent dynamic information due to the orthogonality of wavelet functions. Wavelet transform and wavelet packet in tandem with some signal processing methods, such as autoregressive spectrum, energy monitoring, fractal dimension, etc., can produce many desirable results for condition monitoring and fault diagnosis of machinery. Nonstationary fluctuation was extracted, weak defect of ball bearings was detected from the vibrations and latent fault diagnosis was realized at the early stage. Energy condition monitoring and fractal dimension analysis for nonlinear looseness fault were introduced.