10.21 THE USE OF ARTIFICIAL INTELLIGENCE IN TRAIN TRAFFIC MANAGEMENT TASKS - Djabbarov Saidurhan Tolaganovich Tashkent State transport university t.f.d., professor Yunusov Yo’ldoshali Zhuraboyevich head of the full-time Education Department of the Tashkent State Transport Technical School Razzakov Mashrab Evanovich (Innovative technologies in construction Scientific Journal, 2024)
This article talks about artificial intelligence it is extremely important to define it. Artificial intelligence is the ability of a digital computer or a computer-controlled robot to perform tasks normally associated with intelligent beings. In addition, the definition of artificial intelligence is reduced to describing a complex of interrelated technologies and processes, such as machine learning, virtual agents and expert systems. Key words: artificial intelligence, smart locomotive, transport resources, intelligent diagnostics, control system. Intelligent railway systems are becoming more widespread in world practice. Modern tools such as hybrid models have given a powerful impetus to their development, artificial intelligence, machine learning and deep learning, and others. These technologies make it possible to optimize transport resources, thereby increasing the efficiency of transportation. In many developed countries, the development of transport is currently based on the design of a new generation of rolling stock and implementation of intelligent control systems by the transport complex. Moreover, the introduction of integrated systems using artificial intelligence is relevant for all types of transport. The following systems were selected for the study: A smart locomotive and an Intelligent control system for railway transport. "Smart Locomotive" is a system for intelligent repair of locomotives by condition. The most important task in the operation of railway traction rolling stock is monitoring and forecasting its technological characteristics, planning and optimizing predictive repairs, taking into account the infrastructural and technological limitations of public railway transport [2]. The Smart Locomotive system identifies approaching equipment failures several weeks or months before they occur. This valuable information gives the customer the opportunity to transform the equipment repair process into a state-of-the-art process. Clover Group has developed and implemented a system for intelligent diagnostics and forecasting of the technical condition of locomotive equipment. The anomaly search module is now implemented on 4000 sections. The Clover system finds more than 60 types of equipment malfunctions and analyzes more than 20 types of equipment: traction generators, traction electric motors, fuel pumps, oil pumps, radiators water, turbochargers, rheostatic brakes and others. During the period of pilot operation, the system processed 2,000,000 data operating hours of locomotives, more than 120,000 were automatically found incidents in the operation of locomotive equipment. The solution integrates with The customer’s ERP system: production orders are formed automatically, based on data about incidents and failures. This makes it possible to calculate the resources needed for repairs and in a timely manner update the schedule of locomotives entering the depot to perform scheduled and unscheduled repairs [3]. As a result of using the solution, the reliability and safety of locomotives on the lines have been increased – failures on the line have been reduced by 32%. The time for locomotive diagnostics has been reduced from 4 hours to 10 minutes.