The Development of a Diagnostics Complex for the Metro Electric Rolling Stock Using Thermal Imaging and Electronic Devices

Purpose: To develop a concept for a diagnostics complex for the electric rolling stock in the Metro system using thermal imaging and electronic means. To investigate the implementation of modern non-destructive testing methods, including thermal imaging and artificial intelligence (AI) technologies for the diagnostics of the Metro electric rolling stock. To demonstrate the advantages of the aforementioned methods in comparison with traditional approaches. To justify their application for improving the rolling stock operation safety and efficiency. Methods: Analysis of the contemporary methodologies employed in the field of non-destructive testing, such as magnetic powder, ultrasonic, eddy current, and capillary testing, and their limitations. The investigation of modern technologies, including thermal imaging and machine vision systems with artificial intelligence. Results: The limitations of conventional non-destructive testing methodologies have been elucidated, encompassing their restricted applicability to non-magnetic materials, the necessity for contact zones, and the susceptibility to interference. The merits of thermal imaging and AI technologies have been demonstrated, including remote accessibility, enhanced precision, the capacity for early defect detection, and the automation of processes. A comprehensive approach to the rolling stock diagnostics has been proposed, combining thermal imaging and electronic devices. A block diagram of a diagnostics complex for Nevskoe electric train depot using thermal imaging and electronic devices has been developed. Practical significance: The implementation of contemporary control methodologies has the potential to transform the paradigm of maintenance practices, transitioning from scheduled preventive measures to a predictive maintenance model. This transition is expected to engender a range of benefits, including reduced expenditure on repairs, minimized downtime, and enhanced traffic safety. The proposed diagnostic system has the capacity to be adapted to other depots and transport systems.