MOMEDA and compressed sensing rolling bearing fault diagnosis method

The invention discloses an MOMEDA and compressed sensing rolling bearing fault diagnosis method, and relates to the technical field of intelligent detection. The method can perform intelligent diagnosis on an early fault bearing under the condition that the bearing is not disassembled, and huge pressure caused by data storage, signal transmission and subsequent data processing on related hardware can be relieved through the implementation of compressed sensing software. The specific scheme is as follows: the method comprises the following steps: S1, collecting an original signal; S2, carrying out noise reduction preprocessing on the original signal; S3, taking a K-SVD dictionary learning algorithm as a sparse representation method of the signals; S4, carrying out compression measurement on the sparse signal processed in the S3; S5, carrying out precise reconstruction on the compressed signal processed in the step S4, and obtaining a reconstruction error; S6, comparing the reconstruction errors of the same sam