Picture of mobile phone running fintech app

Fintech: Open Access research exploring new frontiers in financial technology

Strathprints makes available Open Access scholarly outputs by the Department of Accounting & Finance at Strathclyde. Particular research specialisms include financial risk management and investment strategies.

The Department also hosts the Centre for Financial Regulation and Innovation (CeFRI), demonstrating research expertise in fintech and capital markets. It also aims to provide a strategic link between academia, policy-makers, regulators and other financial industry participants.

Explore all Strathclyde Open Access research...

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.

[img]
Preview
Text (Unanue-Catterson-ICICIS2015-Probabilistic-model-checking-for-the-verification-of-prognostics-applications)
Unanue_Catterson_ICICIS2015_Probabilistic_model_checking_for_the_verification_of_prognostics_applications.pdf
Accepted Author Manuscript

Download (626kB) | Preview

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.