{"title":"On the use of probabilistic model-checking for the verification of prognostics applications","authors":"J. Aizpurua, V. Catterson","doi":"10.1109/INTELCIS.2015.7397225","DOIUrl":null,"url":null,"abstract":"Prognostics aims to improve asset availability through intelligent maintenance actions. Up-to-date remaining useful life predictions enable the optimization of maintenance planning. Verification of prognostics techniques aims to analyze if the prognostics application meets the design requirements. Online prognostics applications depend on the data-gathering hardware architecture to perform correct prognostics predictions. Accordingly, when verifying prognostics requirements compliance, it is necessary to include the effect of hardware failures on prognostics predictions. In this paper we investigate the use of formal verification techniques for the integrated verification of prognostics applications including hardware and software components. Focusing on the probabilistic model-checking approach, a case study from the power industry shows the validity of the proposed framework.","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"51 1","pages":"7-13"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INTELCIS.2015.7397225","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Prognostics aims to improve asset availability through intelligent maintenance actions. Up-to-date remaining useful life predictions enable the optimization of maintenance planning. Verification of prognostics techniques aims to analyze if the prognostics application meets the design requirements. Online prognostics applications depend on the data-gathering hardware architecture to perform correct prognostics predictions. Accordingly, when verifying prognostics requirements compliance, it is necessary to include the effect of hardware failures on prognostics predictions. In this paper we investigate the use of formal verification techniques for the integrated verification of prognostics applications including hardware and software components. Focusing on the probabilistic model-checking approach, a case study from the power industry shows the validity of the proposed framework.
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