Intelligent Monitoring And Fault Diagnosis System Of Research For The Metro Station's Equipments

In large cities, urban metro is the first choice for day-to-day transport trips, played an important role. It has a convenient, fast, safe, comfortable, and so on. The reliability of metro station equipments is great significance in the normal operation of subway. Metro station equipments mainly provide a safe and comfortable traveling environment for passengers. Metro will be composed of 17 lines in shanghai, so the network operation must taken into account the issue of resource sharing. The sharing of resources, including equipments and systems of the lines, will make for saving a limited land resources and promoting process and society of maintenance of equipments.In the thesis, the method of resource sharing of station equipments in the metro network operation is put forward based on research of the monitoring system at present and in the further for metro. In the case of the maximum extent keeping the existing station equipments the hardware environment, design of embedded controller for the station equipments achieves resource sharing between station equipments and information resources of the different lines, so it improve the safety of the station equipment and effectively reduce construction and operating costs. Station controller is designed using Windows platform, and the intelligent monitoring system of station equipments for metro is designed using China-made configuration software.In the case of management of station equipment for urban metro, the intelligent management systems is put forward based on the study of the existing management system for station equipment. In the intelligent management system of station equipments, the functions are increased about the early warning and diagnosis of equipments failure. The model of early warning and diagnosis of equipments failure is set up based on multi-sensor information fusion technology of neural network. The diagnostic model of equipments failure can effectively provide a decision-making for the maintenance of equipment failure and real-time health status for the station equipments, to achieve the on-demand maintenance of the maximum extent and reduce operating costs. The equipments of occurred failure can use diagnostic results to quickly repair, reduce downtime and improve safety of the traveling.