System of Remote Monitoring of Technical Objects

Currently, digitalization, being implemented in all spheres of human activity, including transport processes, requires efficiency in obtaining and processing information, as well as timeliness of decisions made on its basis. The modern system of operation of railway traction rolling stock is characterized by the lack of online information about the current technical condition and the residual life of its components for decision making.

The article proposes to solv e the problem by implementing an adaptive system for remote online monitoring of technical parameters of operated objects into the field of traction rolling stock operation. The adaptive system contains software related to recommendation decision support systems. A distinctive feature of the system is the presence of elements of artificial intelligence, which self-learns by combinatorial processing of the historical database on operation of this or a similar technical object and current performance indicators corresponding to them.

The proposed information processing algorithm is versatile and, in principle, can work with a variety of data sources, including existing traction rolling stock safety devices. Online monitoring of technical parameters of operated objects can be extended to both cargo-passenger rolling stock and related auxiliary machinery and devices (track machines, cranes, hump retarders, etc.). Based on the analysis of the information received, the software generates and transmits recommendations regarding current urgent actions for managing staff and maintenance personnel.

In addition, the proposed technology makes it possible to predict indicators of accidents at operated objects in real time, providing an opportunity to facilitate the diagnostic process, optimize organisation of maintenance, reduce the cost of maintaining rolling stock, and increase safety of the transportation process.

The adaptive system of remote online monitoring of operational safety of technical objects, considered in the article, through a risk-based approach, is a unique development that has no analogues. 

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