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

Abstract EN

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.