Affiliation of Author(s):自动化学院

Journal:2017 CHINESE AUTOMATION CONGRESS (CAC)

Key Words:traction motor Kernel SVM EEMD incipient fault diagnosis closed-loop system

Abstract:In this paper, the incipient fault diagnosis problem is studied for traction motor sensor fault. The data used for the fault diagnosis is from sensors of the closed-loop traction motor system, in which the deviations between normal and bias faulty data are of 1%similar to 5% and between normal and gain faulty data are of 1%similar to 10%. Considering the non-stationary of the data, the Ensemble Empirical Mode Decomposition method is used to transform the original data to intrinsic mode functions (IMFs). Then, the fault feature vector is extracted from IMFs. To deal with the fault diagnosis problem, the kernel support vector machine is utilized to be trained by the feature vector, and achieve the classification of the feature vector. The simulation results show that incipient faults can be diagnosed completely by the Kernel SVM based on EEMD method.

Translation or Not:no

Date of Publication:2017-01-01

Co-author:Sun, Xiuwen,Jiang Bin,Li, Min

Correspondence Author:mzh