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Open AccessArticle

A Network Method for Identifying the Root Cause of High-Speed Rail Faults Based on Text Data

1
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
2
Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education, School of Information, Renmin University of China, Beijing 100872, China
*
Author to whom correspondence should be addressed.
Energies 2019, 12(10), 1908; https://doi.org/10.3390/en12101908
Received: 21 April 2019 / Revised: 13 May 2019 / Accepted: 14 May 2019 / Published: 18 May 2019
(This article belongs to the Special Issue Fault Diagnosis and Fault-Tolerant Control)
Root cause identification is an important task in providing prompt assistance for diagnosis, security monitoring and guidance for specific routine maintenance measures in the field of railway transportation. However, most of the methods addressing rail faults are based on state detection, which involves structured data. Manual cause identification from railway equipment maintenance and management text records is undoubtedly a time-consuming and laborious task. To quickly obtain the root cause text from unstructured data, this paper proposes an approach for root cause factor identification by using a root cause identification-new word sentence (RCI-NWS) keyword extraction method. The experimental results demonstrate that the extraction of railway fault text data can be performed using the keyword extraction method and the highest values are obtained using RCI-NWS. View Full-Text
Keywords: information extraction; root cause identification; railway fault; complex network; text data information extraction; root cause identification; railway fault; complex network; text data
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Yang, L.; Li, K.; Zhao, D.; Gu, S.; Yan, D. A Network Method for Identifying the Root Cause of High-Speed Rail Faults Based on Text Data. Energies 2019, 12, 1908.

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