Abstract
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.
Highlights
Against the backdrop of great development of rail transit construction of China, subway tunnel diseases are getting worse and are commonly seen in the operating tunnels
We proposed the tunnel disease association rule mining algorithm based on the support degree
Referring to the relevant documents and combining with the practice of prevention and control of the tunnel diseases, this paper took the elementary event of Ig(i) > 0.4 as the mining object of the association mechanism of the tunnel diseases: X17: high temperature; X2: unallocated personnel; X1: personnel slack; X12: bad weather X13: lamp fault; X4: maintenance error Through calculation of the occurrence probability of the tunnel diseases and importance analysis of the elementary events, we obtained the major object for mining the association mechanism of the subway tunnel diseases
Summary
Against the backdrop of great development of rail transit construction of China, subway tunnel diseases are getting worse and are commonly seen in the operating tunnels. The subway management department has detected the tunnel safety indicator data every year and collected a huge amount of data These data are basically unused and have yet to play an effective role in the prediction and control of the diseases. The management department invests lots of manpower, material resources, and funds into maintenance and control of the tunnel diseases every year, great improvement still has not been seen in the tunnel disease condition; sometimes even fatal accidents may be caused. This has drawn attention of the relevant departments. It is necessary to conduct in-depth analysis of the subway tunnel diseases and their association mechanism
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