RESEARCH ON FAULT DIAGNOSIS METHOD OF ROLLING BEAR BASED ON SYMBOLIC ANALYSIS OF INTRINSIC MODE FUNCTION

Abstract

A fault diagnosis method of the intrinsic mode components symbolic analysis is proposed on the basis of empirical mode decomposition. Firstly,the extension fault signal is decomposed into several intrinsic mode functions under different time scales with empirical mode decomposition. Secondly,analyze the symbolization of intrinsic mode functions in order to find relationship between different faults hidden in them. At last,calculate entropy of symbolized sequence to establish a characteristic vector which can express fault in some way. And then realize the fault diagnosis with the help of some kind of pattern recognize method. The results show that there is a good recognition effect for typical bearing fault and printing machine fault. Bearing failures in offset printing under different rotational speed are detected successfully. The method has a good effect at features extraction in time domain and reduces computation in frequency domain compare with similar research. The symbolic entropy has good application prospects in engineering.

Keywords

• Rolling bear;Fault diagnosis;Empirical mode decomposition;Symbolic signal