Extraction of week impulse fault signal based on sparse decomposition

Aimed at the problem of extraction for week impulse signal in rolling bearings, a method of week impulse fault signal extraction based on sparse decomposition is proposed. The over-complete dictionary is divided into a number of sub dictionaries, and calculate the coherent coefficient accumulation with the fault vibration signal to get the wave of coherent coefficient accumulation and displacement. According to this wave, the shift factor and frequency factor of the optimal atom can be confirm, then search further to confirm the scale factor and phase factor. Repeat the steps to gain a set of atoms which can represent the fault vibration signal sparsely. This method can extract the week impulses obviously and restrain the low-frequency component and noise effectively with the application of the over-complete dictionary, and can improve the efficiency by analyzing the relevance between the wave of coherent coefficient accumulation and the fault signals. The results of simulations show this method is effective and superior.