A Train Fault Diagnosis System Based on C-Means Clustering

Network topological structure of DEMUs with two motor cars and one trailer, fault diagnosis system, fault classification andfault identification by C-Means Clustering Algorithm were introduced. The fault diagnosis system collected and processed information, then,according to the clustering core and...

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Bibliographic Details
Main Authors: SHI Hua, BI Yue-kuan
Format: Article
Language:zho
Published: Editorial Department of Electric Drive for Locomotives 2014-01-01
Series:机车电传动
Subjects:
Online Access:http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2014.01.025
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Summary:Network topological structure of DEMUs with two motor cars and one trailer, fault diagnosis system, fault classification andfault identification by C-Means Clustering Algorithm were introduced. The fault diagnosis system collected and processed information, then,according to the clustering core and the data sample, it produced the sum of square clustering criteria, last, it made decision analysis and outputdiagnostic results. Human machine interface could show the DEMUs fault and record it in files. The fault diagnosis system improved thereliability of the DEMUs and reduced the work of maintenance staff, promoting the train long-term stable running.
ISSN:1000-128X