Abstract
A special intermittent fault was caused by the complex operating environment and the damage of its components in varying degrees in the mechanical equipment system. Thus, it is essential to eliminate the hidden troubles caused by intermittent faults, whose diagnosis method based on sparse representation classification and wavelet packet decomposition (WPD-SRC) is proposed. The energy of every band of multi-channel vibration signals has been extracted by WPD as the feature vector. The sparse learning dictionary was composed of the feature vector of different fault states. The normalized test sample and the sparse dictionary were used as the input of the SRC and for the reconstruction of the error vector with the sparse representation coefficient to diagnose the intermittent fault. The experiment result shows that the intermittent fault can be identified by adopting WPD-SRC, and then what type it belongs to is diagnosed.
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