Research On Safety Evaluation And Risk Management Of High-speed Railway Stations Based On TOPSIS And Bayesian Networks

According to the "Medium-and Long-term Railway Network Plan",it is expected that the nation's high-speed railway will increase to 30,000 kilometers by 2020.At that time,China will enter the new era of high-speed railway known as "eight vertical and eight horizontal".With the construction and development of high-speed railway lines,a series of high-speed railway hubs will be completed and developed into important nodes of an urban integrated transport network.While achieving large-scale passenger flow distribution,high-speed railway passenger stations are also facing new challenges in the station security and passenger transportation organization.Therefore,the evaluation of the safety status of high-speed railway passenger stations,especially the safety control of stations in non-safety status,is an urgent need for the current high-speed railway construction and development,which also has great application value.This paper takes the high-speed railway passenger station as the research object,learns and summarizes the relevant research at home and abroad,and combines risk source identification methods,comprehensive evaluation methods,and Bayesian network analysis methods,using which conduct a scientific,in-depth research on safety assessment and risk control of high-speed railway passenger stations.The research results are as follows:Firstly,it analyzes the safety problems of high-speed railway passenger stations and determines the safety risk factors existing in the operation of high-speed railway passenger stations.Combined with relevant data and expert surveys,six types of high-speed railway passenger stations are identified.Based on the safety accidents of high-speed railway passenger stations,the Fault Tree Analysis is used to analyze the safety risk indicators of high-speed railway passenger stations.Secondly,the cloud model is used to fuzzify the experts' qualitative evaluation language of each station evaluation index.The traditional TOPSIS model is improved and the TOPSIS model of optimal combination weighting is obtained.Based on this,the safety of high-speed railway passenger stations is evaluated.Thirdly,combining the six risk accident trees and Bayesian network theory of high-speed railway passenger stations,the Bayesian network of high-speed railway passenger station security risk events is constructed.The prior probability of network nodes is calibrated based on trapezoidal fuzzy number and Buckley method.Netica software is also used to calculate the posterior probability of each node at the time of accident to control the safety status of high-speed railway passenger stations.Finally,this paper evaluates the safety status of the three high-speed rail stations of Beijing Railway Group Co.,Ltd.,conducts safety risk control and put forward safety improvement suggestions for the station.