Fusion approach for prognostics framework of heritage structure

Rosunally, Yasmine, Stoyanov, Stoyan, Bailey, Chris, Mason, Peter, Campbell, Sheelagh, Monger, George and Bell, Ian (2011) Fusion approach for prognostics framework of heritage structure. IEEE Transactions on Reliability, 60 (1). pp. 3-13. ISSN 0018-9529

Full text not available from this repository.

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
Uncontrolled Keywords: Corrosion, Iron, Monitoring, Predictive models, Bayesian methods, Humidity, Maintenance engineering
Subjects: Computing
Depositing User: Rod Pow
Date Deposited: 17 Sep 2014 11:01
Last Modified: 27 Jul 2017 09:27
URI: http://repository.uwl.ac.uk/id/eprint/942

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