Abstract
In this paper, we consider the possibility of improving the system of monitoring and diagnostics of the railway track in difficult weather conditions, acting on the basis of the analysis of photographic images. The main task of the railway track monitoring system is to ensure safety, functional reliability of the track superstructure, as well as reduce the cost of its maintenance and reduce losses from downtime as a result of failures and premature repairs. An important aspect is the possibility of placing the main elements of the monitoring system on various land transport and technological complexes, and not only on specialized vehicles. This paper is devoted to the functioning of the software control and monitoring system, which allows you to obtain primary information about the object, classify it, identify and group external defects, compare their parameters with the established criteria and issue the processed information to the operator. The considered automated control and monitoring system can be attributed to systems with a continuous cycle. The paper proposes an effective approach for recognizing static and slow-moving objects based on the use of complex primitives, which are formed by constructing multilevel cascades of templates describing the image of an object in the direction of increasing accuracy. Also, to determine the characteristic points of an object, it is proposed a method, which is based on the displacement of an object in the overall picture using the frame framing the search pixel.
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Acknowledgements
This work was supported by the Ministry of Education and Science of the Russian Federation R&D State project № 2.5048.2017/8.9.
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Loktev, D.A., Loktev, A.A. (2020). Automated System for Monitoring the Upper Structure of the Railway Track for Extreme Arctic Conditions. In: Petriaev, A., Konon, A. (eds) Transportation Soil Engineering in Cold Regions, Volume 1. Lecture Notes in Civil Engineering, vol 49. Springer, Singapore. https://doi.org/10.1007/978-981-15-0450-1_21
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DOI: https://doi.org/10.1007/978-981-15-0450-1_21
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