LAUSR

Abstract Sparse representation based on the matching pursuit (MP) algorithm is an effective method for fault feature extraction involving rolling element bearings. However, in the sparse decomposition stage, the MP algorithm is extremely susceptible to both noise in the residual signal and excessive iterations selecting some atoms that are not related to the fault impulses, thus causing interference components in the reconstructed signal. Considering these problems, a secondary selection-based orthogonal MP (SS-OMP) algorithm is proposed in this paper. In the proposed method, all the atoms selected to decompose the residual signal are selected for a second time, and only those atoms directed by the fault impulses are retained. After the decomposition of the residual signal, these retained atoms are used to redecompose the vibration signal, and then the fault impulses in the vibration signal are extracted. The superiority of the proposed method is verified by a numerical simulation study and experimental analysis.