Construction of Railway Foreign Body Intrusion Monitoring System Based on Grid Extraction Algorithm

With the rapid development of high-speed railway and high-speed train technology, the speed of high-speed railway trains and the increase of train density, how to ensure traffic safety becomes more and more important, which puts forward higher requirements for traffic safety guarantee system. At present, railway foreign body intrusion detection technology based on machine vision has become the main research method, especially the recognition algorithm based on supervised learning is widely used. As one of its subsystems, the foreign body intrusion monitoring system of high-speed railway plays an important role. System failure and false alarm will endanger the safety of passengers and trains and affect the running efficiency, so how to analyze and improve the reliability of the system becomes an urgent problem to be solved. Based on the investigation of the disaster monitoring system, this paper analyzes the problems of the disaster monitoring system and summarizes the system faults. Then the fault detection methods are proposed for the main faults. Finally, taking the rainfall monitoring system as an example, the suggestions and measures to improve the system reliability are put forward, and the relevant tests of the system reliability are carried out.