Multi-scale enveloping order spectrogram for rotating machine health diagnosis

This paper presents a hybrid technique to enhance health diagnosis of rotating machines under varying speed conditions. This is achieved through the integration of complex wavelet transform-based envelope extraction of speed-varying vibration signals with computed order tracking for eliminating speed dependence in the sampled data. By performing a post-spectral analysis of the resampled signal, a multi-scale enveloping order spectrogram is realized that has shown to enable enhanced defect feature extraction. Numerical simulation and experimental studies have demonstrated the effectiveness of the hybrid technique in identifying bearing structural defects under varying operating conditions. (C) 2013 Elsevier Ltd. All rights reserved.