Fault detection and diagnosis of bearing based on local wave time-frequency feature analysis

Incipient fault information detection of mechanical equipment is a kind of technical support for efficient operation of current automation equipment. Due to the abruptness and transience of mechanical fault, the traditional signal processing methods based on Fourier transform cannot meet the demands of such kind of transient signals. In this paper, local wave time-frequency analysis techniques are explored, mainly including Signal Denoising, Signal Singularity Detection, Empirical Mode Decomposition (EMD), and the methods for extracting the features of transient signals are also explored, of which the effectiveness is verified by taking the rolling bearing fault as an example.