On the use of probabilistic model-checking for the verification of prognostics applications
Aizpurua, Jose Ignacio and Catterson, Victoria M. (2015) On the use of probabilistic model-checking for the verification of prognostics applications. In: 2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems, 2015-12-12 - 2015-12-14, Ain Shams University. (https://doi.org/10.1109/IntelCIS.2015.7397225)
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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.
ORCID iDs
Aizpurua, Jose Ignacio ORCID: https://orcid.org/0000-0002-8653-6011 and Catterson, Victoria M. ORCID: https://orcid.org/0000-0003-3455-803X;-
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Item type: Conference or Workshop Item(Paper) ID code: 55320 Dates: DateEvent12 December 2015Published26 October 2015AcceptedNotes: (c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
Science > Mathematics > Probabilities. Mathematical statisticsDepartment: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 14 Jan 2016 11:57 Last modified: 11 Nov 2024 16:45 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/55320