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The article presents the results of the research conducted by the authors, the purpose of which was to development a model for recognizing defects in axle caps of a wheel-motor block of a locomotive in order to implement automatic advance notification of management structures about the need for maintenance or repair operations to eliminate defects at an early stage of their occurrence. The research used the following interdisciplinary and mathematical methods: computer and mathematical modeling, methods of mathematical statistics, methods of the theory of artificial intelligence and parametric reliability. As a result of the research, a mathematical formalization of the model for recognizing one of the defects in the axle caps of the wheel-motor block of the locomotive - the groove (chipping) of the babbitt layer was obtained. With the help of the obtained model, it is possible to implement automatic recognition of defects, pre-failure states not only of axle caps, but also of other units of technical systems. The developed model can be used in monitoring systems, control, diagnostics of the technical condition of the locomotive fleet, in order to reduce downtime in repairs and forced costs for scheduled operations. The proposed model solves the range of problems described in the development concept of JSCo Russian Railways associated with the implementation of the actual repair system for the current technical condition of the locomotive, as well as with the digitalization of the company's advanced areas.

The article describes a software module of the initial image processing which allows to perform the contour image analysis in order to find, recognize and evaluate graphic images of various types of inhomogeneities. Application of software module will improve the accuracy of the evaluation of the internal surface of closed vessels in the absence of access control.