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

Linghui Meng, Peizhen Wang, Zhigang Liu, Ruichang Qiu, Lei Wang and Chunmei Xu

Mathematical Problems in Engineering, 2016, vol. 2016, 1-8

Abstract:

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.

Date: 2016
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2016/2358142.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2016/2358142.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:2358142

DOI: 10.1155/2016/2358142

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().