{"title":"Forecasting the Technical Condition and Risks of Construction Engineering Based on Operational Monitoring of Diagnostic Parameters","authors":"V. Zorin, A. Pegachkov","doi":"10.1109/TIRVED56496.2022.9965521","DOIUrl":null,"url":null,"abstract":"In the presented scientific research describes the issues of predicting the technical condition and assessing the risks arising from the operation of construction equipment, based on the analysis of information collected by the remote diagnostics system. This article describes not only the structure of the remote diagnostics system for the technical condition assessment, but also presents a few optimization measures taken to improve the reliability of assessing the technical condition of each object based on the totality of values of controlled parameters. It should be noted that the verification of the performance and reliability of the described forecasting technique was carried out experimentally. And, as a result, the developed system allows predicting the residual resource in real time. The system, using special subsystems with the possibility of self-learning, allows to calculate and predict data on the residual resource of each object connected to the system.","PeriodicalId":173682,"journal":{"name":"2022 Intelligent Technologies and Electronic Devices in Vehicle and Road Transport Complex (TIRVED)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Intelligent Technologies and Electronic Devices in Vehicle and Road Transport Complex (TIRVED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TIRVED56496.2022.9965521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the presented scientific research describes the issues of predicting the technical condition and assessing the risks arising from the operation of construction equipment, based on the analysis of information collected by the remote diagnostics system. This article describes not only the structure of the remote diagnostics system for the technical condition assessment, but also presents a few optimization measures taken to improve the reliability of assessing the technical condition of each object based on the totality of values of controlled parameters. It should be noted that the verification of the performance and reliability of the described forecasting technique was carried out experimentally. And, as a result, the developed system allows predicting the residual resource in real time. The system, using special subsystems with the possibility of self-learning, allows to calculate and predict data on the residual resource of each object connected to the system.