Blind source separation of single-channel mechanical signal based on optimal matching pursuit algorithm

Based on the morphological filter and the characteristics of Matching Pursuit and blind source separation,an underdetermined blind source separation method based on optimal matching persuit algorithm is proposed.Firstly,the collected signal was purified by morphological filter and the noise which affected the diagnosis effect was removed.Then,the matching pursuit(MP) method optimized by genetic algorithm was used to decompose the nonlinear signal into some atom signals in the process of projection separation,thus increasing the matching accuracy and efficiency of the algorithm.These atoms and original observed signals were constituted to construct new observed signals,and then the under-determined problem was transformed into a multi-channel positive definite one.Finally,the Fast kernel independent component analysis(FastKICA) algorithm was used to achieve the separation of the new observed signals,and the failure contribution of different source signals was analyzed.The proposed method can be applied to the simulated signals and real test signals of the rolling bearing.Test results indicate that the mentioned method can well solve the difficult problem of under-determined blind source separation.