{"title":"The Principle of Construction of an Automated System for Monitoring and Diagnostics of Wayside Devices of Railroad Automation and Telemechanics","authors":"E. M. Tarasov, A. E. Tarasova, V. A. Nadezhkin","doi":"10.3103/s1068371223100115","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The architecture of interaction of modules of an automated monitoring and diagnostic system with wayside devices of railway automation and telemechanics is presented. An example of the operation of monitoring system of a rail line condition is considered. Various functions of an automated monitoring and diagnostic system are presented, including monitoring the condition and serviceability of wayside devices, monitoring the resistance of insulating and conductive joints, predicting possible failures, and determining the specific location of their occurrence. The principle of using artificial neural networks for diagnosis and monitoring system is outlined, various neural network training models are considered, and the most appropriate learning model is identified.</p>","PeriodicalId":39312,"journal":{"name":"Russian Electrical Engineering","volume":"40 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3103/s1068371223100115","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
The architecture of interaction of modules of an automated monitoring and diagnostic system with wayside devices of railway automation and telemechanics is presented. An example of the operation of monitoring system of a rail line condition is considered. Various functions of an automated monitoring and diagnostic system are presented, including monitoring the condition and serviceability of wayside devices, monitoring the resistance of insulating and conductive joints, predicting possible failures, and determining the specific location of their occurrence. The principle of using artificial neural networks for diagnosis and monitoring system is outlined, various neural network training models are considered, and the most appropriate learning model is identified.
期刊介绍：
Russian Electrical Engineering is a journal designed for the electrical engineering industry and publishes the latest research results on the design and utilization of new types of equipment for that industry and on the ways of improving the efficiency of existing equipment.
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