Abstract
With the promotion of the national transportation power strategy, super large operation networks have become an inevitable trend, and operational safety and risk management and control have become unavoidable problems. Existing safety management methods lack support from actual operational and production data, resulting in a lack of guidance of fault cause modes and risk chains. Large space is available to improve the breadth, depth, and accuracy of hazard source control. By mining multisource heterogeneous operation big data generated from subway operation, this study researches operation risk chain and refined management and control of key hidden dangers. First, it builds a data pool based on the operation status of several cities and then links them into a data lake to form an integrated data warehouse to find coupled and interactive rail transit operation risk chains. Second, it reveals and analyzes the risk correlation mechanisms behind the data and refines the key hazards in the risk chain. Finally, under the guidance of the risk chain, it deeply studies the technologies for refined control and governance of key hidden dangers. The results can truly transform rail transit operation safety from passive response to active defense, improving the special emergency rail transit operation plans, improving the current situation of low utilization of rail transit operation data, but high operation failure rate, and providing a basis for evidence-based formulation and revision of relevant industry standards and specifications.
Highlights
In recent years, rail transit has achieved rapid development throughout the world
Major potential risks often precede an incident, and incidents are attributed to chained propagation of multiple risks. e risk chain of urban rail transit operation refers an ordered hazard sequence that leads to an unexpected incident during operation because hazards fail to be identified and controlled in time and propagate sequentially, achieving a chain effect
In order to put hazard identification into practice in the information field, Ding conducted an in-depth study on data mining algorithms, built a model for the rail transit dispatching records of a certain supercity to identify the major rain transit hazards, and developed an intelligent hazard identification system based on the data warehouse [12]. e concept of chained risk propagation originates from the fields of project management, trade finance, media, public opinion, culture, etc. but has not yet been extensively studied in the field of rail transit safety management
Summary
Rail transit has achieved rapid development throughout the world. Incidents on such large rail transit networks are highly likely to cause secondary damage and even derivative disasters, which may propagate in a chained manner. In order to put hazard identification into practice in the information field, Ding conducted an in-depth study on data mining algorithms, built a model for the rail transit dispatching records of a certain supercity to identify the major rain transit hazards, and developed an intelligent hazard identification system based on the data warehouse [12]. Ere are a few arithmetic studies on hazard identification in the field of railway traffic and mining engineering, but most of them focus on the accident tree method and association rule algorithm. (iii) Extensive research on big data and data mining algorithms has been conducted in China, but it mainly focuses on commercial purposes or bank loan risk assessment, with very few conclusions about rail transit safety management. It is necessary to build data mining algorithms to provide methodological guidance for hazard identification related to rail transit operation. (iv) Research on risk control algorithms and measures mainly focuses on risk control in industrial engineering and mining engineering. e control measures are mostly applied to information-based management, whereas the preliminary risk assessment and hierarchical control are less refined, making it difficult to avoid careless omissions when an incident occurs
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