| Time-frequency analysis, including wavelet transforms, is one of the new and powerful tools in the important field of structural health monitoring using vibration analysis. Commonly-used signal analysis techniques, based on spectral approaches such as the Fast Fourier Transform (FFT), are powerful in diagnosing a variety of vibration-related problems in rotating machinery. Although these techniques provide powerful diagnostic tools in stationary conditions (steady mode), they fail to do so in several practical cases involving non-stationary data (transient mode), which could result either from fast operational conditions, such as the fast start-up of an electrical motor, or from the presence of a fault causing a discontinuity in the vibration signal being monitored.; Although the short-time Fourier transform (SIP 0 dose provide the classical FFT with a capability of retrieving some time information through its use of windowing, it remains incapable of inquiring the FFT s frequency resolution beyond what the window used can offer, especially for localized (transient) signals.; This thesis addresses the problem of detecting impulsive faults in turbo-machinery using a novel approach combining three powerful signal processing tools: the wavelet packet transform, continuous wavelet transform and maxima lines in wavelet domain. The test used in this thesis consists of a lab-grade experimental setup of vibration analysis. Related and critical issue such as the selection of mother wavelet is also addressed. Finally the results are very encouraging in that the targeted impulsive faults have been accurately and effectively detected. |
