Research on Fault Diagnosis of Rotating Machinery of Vehicle Transmission

Abstract

Abstract. In this paper, the gearbox as the research object, under the conditions of strong interference signal acquisition and analysis, denoising, eigenvalue extraction, pattern recognition and fault prediction has very important practical significance. Aiming at the problem of end effect in Empirical Mode Decomposition (EMD), an improved method for the continuation of the even-extended cosine window function (EECW) of signal sequences is proposed. Firstly, the signal sequence is continually extended to realize the smooth transition between the extension data and the original signal, avoiding the jump of the instantaneous frequency of the signal. Secondly, there is the problem of continuation error for this extension method. (Or slow speed) to the internal development of data to ensure the correct decomposition of the signal valid data to improve the accuracy of the decomposition of the signal to achieve the improvement of EMD algorithm. Through the simulation analysis and fault diagnosis, it is shown that the method can effectively suppress EMD endpoint effect and realize the effective diagnosis of rotating machinery fault. The experimental results show that the proposed method has high precision and good performance