Decision Making Based on the Results of Automatic Diagnostics of Parts and Assemblies of Rolling Stock

The article reviews a preventive maintenance system for repairs, the main disadvantage of which is that it is essentially an open system of technical control that does not take into account objective assessment of rolling stock «as it is». The objective of the study was to review and summarize the existing researches and to word the proposals to develop the system of rolling stock maintenance. Based on the analysis of the researches in that field it is proposed to reduce material and labor costs for maintenance of cars by making the system of technical diagnostics closed. As a feedback, it is advisable to use an automatic test diagnostic control system that detects car defects while the train is running. It will significantly reduce the number of manual operations for inspecting rolling stock in the arrival parks of sorting stations and automate decision-making on possibility of subsequent operation of controlled rolling stock based on its actual condition. A technique is proposed for evaluating the results of technical diagnostics of rolling stock in which probabilistic estimates are used, dividing the most significant defects of the controlled object into three classes according to the degree of their significance for operation safety. It has been established that Weibull distribution corresponds to fatigue defective phenomena, while Rayleigh distribution corresponds to wear phenomena with constant or periodic workload. To identify defective car wheels and axle boxes, a dynamic system is proposed, which includes: the controlled object which is a wheel or axle box, automatic test diagnostic equipment and a resolver for deciding on further operation of the identified defective car. The optimal equation of the separating function of «false alarm» and «acceptance» is obtained on the basis of the Bayes criterion, which minimizes the average risk of making a wrong decision.