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In this paper, a RQA-based approach is developed for feature generation from raw vibration data recorded from a rotating machine with five different conditions. The created features are then used as the inputs to a classifier for the identification of six bearing conditions. Experimental results demonstrate the ability of RQA to discover automatically the different bearing conditions using features...
Analysing vibration signal is an effective important method for diesel engine fault diagnosis, and its key techniques are feature extraction and pattern recognition. In this paper, wavelet packet decomposition algorithm as an effective method for fault feature extraction is used to decompose the vibration signals, and its percentage of energy band wavelet packet and wavelet packet energy spectrum...
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