{"title":"Parameter control and forecast for electric drive parameters of cutter-loader","authors":"D. Shprekher, G. I. Babokin, E. Kolesnikov","doi":"10.1109/ICIEAM.2017.8076303","DOIUrl":null,"url":null,"abstract":"We propose a new system for control of an electric drive of the cutter-loader greatly improving its operational reliability and safety. The problem is solved by forecast of electric and mechanical diagnostic indicators of the electric drive and implementation of predictive control activities related to maintenance and repair based on actual technical conditions. Forecasting drive parameters is enabled with a neural network model. It increases the mean time between failures and availability factor of the electric drive compared with operation of the control system without a parameter prediction feature.","PeriodicalId":428982,"journal":{"name":"2017 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIEAM.2017.8076303","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
We propose a new system for control of an electric drive of the cutter-loader greatly improving its operational reliability and safety. The problem is solved by forecast of electric and mechanical diagnostic indicators of the electric drive and implementation of predictive control activities related to maintenance and repair based on actual technical conditions. Forecasting drive parameters is enabled with a neural network model. It increases the mean time between failures and availability factor of the electric drive compared with operation of the control system without a parameter prediction feature.