Design And Implementation Of Core Modules Of Intelligent Operation And Maintenance System For Subway Trains Based On Big Data Technology

With the rapid development of urbanization,urban rail transit has gradually become the main force of transportation in large and medium-sized cities by virtue of its advantages of large size,high efficiency and environmental protection.To cope with the increasing ridership,subway operators have been increasing the number of trains in operation.How to reduce operation and maintenance costs and improve operation and maintenance management efficiency on the premise of ensuring safe and stable operation has become an urgent problem for urban rail transit.Limited by the traditional operation and maintenance system and maintenance management mode,rail transit operation enterprises in major cities basically choose the maintenance mode of planned maintenance and state maintenance.The traditional maintenance mode has problems such as low efficiency,high cost and excessive maintenance.resulting in low operation and maintenance efficiency of subway trains,which is difficult to meet the needs of reliable and economic operation and maintenance.Intelligent vehicle operation and maintenance system uses advanced monitoring and perception,cloud computing,Internet of Things,big data and other technical means to realize real-time monitoring,fault prediction and health assessment of subway trains,so as to ensure the safety of vehicle operation,promote the transformation of enterprise operation and maintenance mode,and achieve cost reduction and efficiency increase of subway train operation and maintenance.The main research work of this paper is as follows:(1)Based on the high-throughput data of subway trains,a hybrid architecture of distributed message queue and big data processing engine is adopted to realize real-time receiving and analysis of high-throughput subway train data.(2)Construct the ground warning model of subway train doors.By analyzing the door landing data of urban metro trains,three dimensions of door opening consistency,door closing consistency and total time of door opening and closing are selected to construct the door characteristic index.The mean and variance of the door opening and closing anomaly index are calculated through the statistics of the opening and closing anomaly index of all trains in a period of time.The deviation degree of variance and mean is used to determine whether the door is abnormal.(3)The health evaluation method of subway trains was preliminarily established.The weight weight of each subsystem is constructed according to the order of the influence of each subsystem on the vehicle safety by AHP.The health status of the subsystem is scored by using the sub-component warning model,failure mode and hazard influence.The health degree of the subsystem is further obtained.