Rosunally, Y.Z., Stoyanov, S. ORCID: https://orcid.org/0000-0001-6091-1226, Bailey, C. ORCID: https://orcid.org/0000-0002-9438-3879, Mason, P., Campbell, S., Monger, G. and Bell, I. (2011) Fusion approach for prognostics framework of heritage structure. IEEE Transactions on Reliability, 60 (1):570453. pp. 3-13. ISSN 0018-9529 (doi:10.1109/TR.2011.2104451)

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Abstract

The Cutty Sark is undergoing major conservation to slow down the deterioration of the original Victorian fabric of the ship. While the conservation work being carried out is “state of the art,” there is no evidence at present of the effectiveness of the conservation work over the next fifty years. A prognostics framework is being developed to monitor the “health” of the ship's iron structures to help ensure a 50 year life once conservation is completed, with only minor deterioration taking place over time. This paper presents the prognostics framework being developed, which encompasses four approaches: 1-Canary and Parrot devices, 2-Physics-of-Failure (PoF) models, 3-Precursor Monitoring and Data Trend Analysis, and 4-Bayesian Networks. “Canary” and “Parrot” devices have been designed to mimic the actual mechanisms that would lead to failure of the iron structures, with canary devices failing faster to act as an indicator of forthcoming failures, while parrot devices fail at the same rate as the structure under consideration. A PoF model based on a decrease of the corrosion rate over time is used to predict the remaining life of an iron structure. Mahalanobis Distance (MD) is used as a precursor monitoring technique to obtain a single comparison metric from multiple sensor data to represent anomalies detected in the system. Bayesian Network models are then used as a fusion technique, integrating remaining life predictions from PoF models with information of possible anomalies from MD analysis to provide a new prediction of remaining life. This paper describes why, and how the four approaches are used for diagnostic and prognostics purposes, and how they are integrated into the prognostics framework.

Item Type:	Article
Additional Information:	[1] Date of Publication: 31 January 2011. Date of Current Version: 28 February 2011. [2] Article No. 5704534.
Uncontrolled Keywords:	probabilities, prognostics framework, computer modelling, Cutty Sark, conservation
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Pre-2014 Departments:	School of Computing & Mathematical Sciences School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Computational Mechanics & Reliability Group
Related URLs:	Publisher Organisation
Last Modified:	13 Mar 2019 11:33
URI:	http://gala.gre.ac.uk/id/eprint/6902

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