Research On Vulnerability Analysis And Risk Dynamic Control Of Subway Station Safe Operation

Subway plays an important role in facilitating people's travel,alleviating rail traffic congestion,saving energy,and accelerating urban economic development.The subway station,which is at the core of the subway,not only bears the high density of people,but also concentrates a large number of modern facilities and equipment.Its safe operation is an important guarantee for the safety of the entire subway system.Because the subway station is constantly disturbed by various random and uncertain factors,these factors have different degrees of causing different safety accidents,and the impact on the safety level has the characteristics of time series dynamics and nonlinearity.Therefore,it is necessary to make an in-depth analysis of the safety operation characteristics and the formation mechanism of the vulnerability of the subway station,scientifically and rationally evaluate the safety state and make corresponding measures to reduce the adverse effects of random factors on the state and avoid the most serious fire accidents.By comparing the principle and applicable scope of various accident-causing models,and combining with the characteristics of the subway station operation,The 2-4 Model with system characteristics is adopted to analyze the formation mechanism of operation vulnerability in the subway station system.The path of fire accident is drawn by combining the causative chain of guiding behavior,operating behavior,habitual action,one-time behavior and material state.Combining with regulations and relevant studies,the precursor characteristics of subway station safety operation vulnerability are identified to simplify the accident path.Based on the normal grey cloud theory,the qualitative concepts of feature Banks are quantified as probability distribution,and the influence relationship between feature Banks is quantified with the data mining theory,which provides a data basis for thevulnerability evaluation of subway stations.Based on the fuzzy Petri net,a dynamic evolution model of subway station safety operation risk is constructed to evaluate the subway operation safety state.At the same time,through forward reasoning,the dynamic propagation path of risk is deduced,and reverse reasoning realized the identification and control of risk.According to the inefficiency of the safety and dynamic changes of subway stations,the potential law of passenger flow impact is tapped to obtain the predicted value.Combined with the change law of statistical forecast deviation of time information,Markov theory is introduced to modify the impact of passenger flow to achieve short-term prediction of the status of subway stations.An improved fuzzy Petri net evaluation model and a modified Markov prediction model are used to analyze the safety operation status of a subway station.The evaluation results show that the safety status level is “Alert”.Combining the evaluation results,corresponding control suggestions are proposed from four aspects: improvement of building space,improvement of personnel management,popularization of publicity knowledge and improvement of emergency plans.It is hoped that the research work of the thesis has practical significance for enriching the safety operation risk management system of subway stations.