Subway Tunnel Disease Associations Mining Based on Fault Tree Analysis Algorithm
Joint Authors
Ding, Xiaobing
Hu, Hua
Huang, Qiuyu
Zhu, Haiyan
Liu, Zhigang
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-01
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Monitoring and control of subway tunnel diseases throughout operation determine whether the operation of the subway is safe or not.
In order to ensure operation safety, in-depth analysis of tunnel disease risks must be conducted.
We constructed a fault tree based on tunnel diseases of Shanghai Subway at first.
Using the subway tunnel maintenance work data, we calculated the probability of occurrence of elementary events of the fault tree, conducted quantitative calculation and analysis on the tunnel diseases, and found major diseases of the tunnels and their causes in light of the calculation results.
Then, indicated by the precise fault tree analysis (FTA) we conducted, common tunnel diseases mainly include large passenger flow, shortage of maintenance personnel, maintenance error, personal carelessness, hot weather, and poor lighting.
Analysis was conducted on the probability importance of elementary events of the tunnel diseases as well.
In the end, we proposed the tunnel disease association rule mining algorithm based on the support degree.
Via the calculation of association among major diseases, we explored the elaborate association mechanism of the diseases.
The in-depth mining on the association mechanism can provide theoretical support and decision support for prevention and comprehensive control of the tunnel diseases and lay a solid foundation of practice guidance for subway operation safety of megacities.
American Psychological Association (APA)
Ding, Xiaobing& Huang, Qiuyu& Zhu, Haiyan& Hu, Hua& Liu, Zhigang. 2017. Subway Tunnel Disease Associations Mining Based on Fault Tree Analysis Algorithm. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1189886
Modern Language Association (MLA)
Ding, Xiaobing…[et al.]. Subway Tunnel Disease Associations Mining Based on Fault Tree Analysis Algorithm. Mathematical Problems in Engineering No. 2017 (2017), pp.1-7.
https://search.emarefa.net/detail/BIM-1189886
American Medical Association (AMA)
Ding, Xiaobing& Huang, Qiuyu& Zhu, Haiyan& Hu, Hua& Liu, Zhigang. Subway Tunnel Disease Associations Mining Based on Fault Tree Analysis Algorithm. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1189886
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1189886