Research on Safety Inspection Technology of High-Speed Railway Catenary System Combined with Kalman Filtering

The fault detection of high-speed railway catenary is usually carried out by safety inspection device (C2 system) plus manual inspection, which is low efficiency and high cost. In order to improve the efficiency of inspection and reduce the cost of inspection, a target tracking algorithm is constructed by combining Kalman filtering algorithm and Meanshift algorithm to achieve efficient and fast target tracking. The triangle image of catenary cantilever device of high-speed railway is extracted completely, and the RBF neural network is used for image fault recognition. The research results show that the accuracy of catenary fault identification can reach 95% after using the target tracking algorithm. The above results show that the target tracking algorithm can effectively improve the safety inspection efficiency of high-speed railway catenary and reduce the cost.