| Railway safety is the top priority of railway transportation production and management,it is directly related to the national economy and people’s livelihood.With the rapid development of high-speed railways and the gradual improvement of railway information construction,China’s railway has accumulated a large amount of safety data,and all kinds of data is increasing rapidly.China’s railway has entered the era of big data,and the continuous progress of big data technology has brought new possibilities for railway safety.Vehicle equipment is the core part of rail transit,because the health status of vehicle equipment directly affects railway operation.The causes of railway accidents mainly come from the "human" factor and the "equipment" factor,therefore,how to avoid "unstable state " and prevent accidents and faults from the perspective of "material prevention" has become an urgent problem for the railway industry.The(UIC)railway security bulletins report 2017 pointed out that the causes of railway accidents mainly come from the "human" factor and the "equipment" factor,therefore,how to avoid "unstable state of equipment and human " and prevent accidents and faults from the perspective of "material prevention" and "human prevention" has become the urgent problem for the railway industry.Vehicle equipment is the core part of rail transit,because the health status of vehicle equipment directly affects railway operation.From the perspective of "material prevention",the vehicle equipment health status evaluation is based on the integration of massive data,such as basic equipment records,dynamic examination records,maintenance records,and historical records of accidents and etc.Therefore,a comprehensive visual model of vehicle equipment can be constructed and using information of the status,alarm and faults,safety prediction can be modeled and analyzed to avoid “unstable state”,preventing accidents and faults in advance.This paper based on big data safety application project,verifies vehicle equipment health status assessment index system through discussion with experts on filed,proposes health status prediction and evaluation model for rolling stocks,and finally achieves the module of comprehensive analysis of equipment health condition in big data safety application platform.This platform can effectively increase communication among vehicle systems to support monitoring and decision-making for vehicle department in bureaus.The paper includes the following aspects:1.Construct vehicle equipment,(including passenger car,rolling stocks,freight car,and 5T),health status assessment index system;2.Taken data from one car depot as an example,combined with traits of rolling stocks,construct health status assessment regression model for rolling stocks;3.Through time series algorithms build prediction models for every dimension of vehicle respectively;construct health status prediction and evaluation model for rolling stocks,based on the health status assessment model mentioned above;4.Accomplished as a module of comprehensive analysis of equipment health condition in big data safety application platform.Introduce the central functions of this module,verify its system structure,important techniques and etc.,and evaluate the application of big data safety application platform. |
