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Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 2358142, 8 pages
Research Article

Safety Assessment for Electrical Motor Drive System Based on SOM Neural Network

School of Electrical Engineering, Beijing Jiaotong University, Beijing Engineering Research Center of Electric Rail Transportation, Beijing 100044, China

Received 19 December 2015; Accepted 16 February 2016

Academic Editor: Wen Chen

Copyright © 2016 Linghui Meng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


With the development of the urban rail train, safety and reliability have become more and more important. In this paper, the fault degree and health degree of the system are put forward based on the analysis of electric motor drive system’s control principle. With the self-organizing neural network’s advantage of competitive learning and unsupervised clustering, the system’s health clustering and safety identification are worked out. With the switch devices’ faults data obtained from the dSPACE simulation platform, the health assessment algorithm is verified. And the results show that the algorithm can achieve the system’s fault diagnosis and health assessment, which has a point in the health assessment and maintenance for the train.