System for Periodic Monitoring of Railway Automation and Remote Control Facilities Based on Unmanned Aerial Vehicles

Modern diagnostic information collection systems do not allow obtaining a complete set of diagnostic data on the floor-mounted technological equipment of railway automation and remote control. This is due to the technical features of the railway automation and remote control facilities themselves, the conditions of their operation and the technologies of safe data acquisition. The study focuses on improving the principles of obtaining primary diagnostic information on railway automation and remote control facilities using unmanned aerial vehicles. Using methods of discrete mathematics, graph theory, Boolean algebra and technical diagnostics, the study has developed and scientifically substantiated the principles of obtaining diagnostic information on the floor-mounted technological equipment of railway automation and remote control using unmanned aerial vehicles. The unmanned aerial vehicle is equipped with a payload for obtaining diagnostic information on railway automation and remote control facilities located in close proximity to the railway track. The system solves several diagnostic problems at once in relation to the railway automation and remote control system: it collects objective data on the technical conditions of the floor-mounted process equipment (including defects), automates a certain share of routine maintenance operations, and verifies the facts of maintenance work performed by specialised personnel of signalling, interlocking, and blocking divisions. The solution to these problems helps to increase the dependability and safety of railway automation and remote control devices thanks to the timely detection of incipient gradual failures and the prompt identification of already occurred failures that did not manifest themselves during the normal operation of the railway system. It is proposed to integrate data from all existing monitoring systems in a single corporate cloud storage for further processing using a secure intelligent data analytics platform, as well as automatically transfer the results of technical diagnostics to participants in the transportation process for their prompt consideration in train traffic control.

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