Abstract
The goal of the work is to development of a synchronous-replicated model for the assessment of the technical state of a locomotive as a technological system. When performing the work, method of systems analysis, computer and mathematical modelling, artificial intelligence, and mathematical analysis were used. As a result of the research we have obtained a mathematical synchronous-replicated model for the assessment of the technical state of a locomotive based on multilayer neuron forecasting network. The model developed can be used in systems for monitoring, controlling and diagnosing the technical state of the locomotive fleet. This model possesses such novel specific features as low sampling period between quizzing of monitoring facilities, versatility, adaptability and operability. This suggested model resolves a range of tasks set forth in the Concept for the development of the OJSC Russian Railways connected with the implementation of an actual system for repairs and maintenance according to the current condition of locomotives as well as the digitalization of the advanced fields of the company.
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