Giovanni G. C. Chrysostomo, Marco V. B. A. Vallim, L. A. Silva, A. R. A. V. Filho
{"title":"Analytical Workbench: A Framework to Support Predictive Maintenance of Industrial Systems","authors":"Giovanni G. C. Chrysostomo, Marco V. B. A. Vallim, L. A. Silva, A. R. A. V. Filho","doi":"10.1109/CLEI52000.2020.00039","DOIUrl":null,"url":null,"abstract":"This work proposes a framework called Analytical workbench that aims to support the decision making of power generation systems. The framework is structured in three modules. An operational module which receives operating data and prepares it for analysis purposes. The tactical module which allows real time system monitoring. Finally, the strategic module, which allows to make inferences about the future state of the plant's operating data. The results can be seen in a real case study in a Brazilian hydroelectric plant and the main highlights are: identification of faulty sensors, measurement errors, real-time monitoring (every 5 seconds) of all data or just some selected variables and, finally, forecast of the plant's operational status in one more day.","PeriodicalId":413655,"journal":{"name":"2020 XLVI Latin American Computing Conference (CLEI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 XLVI Latin American Computing Conference (CLEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLEI52000.2020.00039","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
This work proposes a framework called Analytical workbench that aims to support the decision making of power generation systems. The framework is structured in three modules. An operational module which receives operating data and prepares it for analysis purposes. The tactical module which allows real time system monitoring. Finally, the strategic module, which allows to make inferences about the future state of the plant's operating data. The results can be seen in a real case study in a Brazilian hydroelectric plant and the main highlights are: identification of faulty sensors, measurement errors, real-time monitoring (every 5 seconds) of all data or just some selected variables and, finally, forecast of the plant's operational status in one more day.