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Erschienen in:
2019 | OriginalPaper | Buchkapitel
VHI: Valve Health Identification for the Maintenance of Subsea Industrial Equipment
verfasst von : M. Atif Qureshi, Luis Miralles-Pechuán, Jing Su, Jason Payne, Ronan O’Malley
Erschienen in: Machine Learning and Knowledge Discovery in Databases
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Abstract
Subsea valves are a key piece of equipment in the extraction process of oil and natural gas. Valves control the flow of fluids by opening and closing passageways. A malfunctioning valve can lead to significant operational losses. In this paper, we describe VHI, a system designed to assist maintenance engineers with condition-based monitoring services for valves. VHI addresses the challenge of maintenance in two ways: a supervised approach that predicts impending valve failure, and an unsupervised approach that identifies and highlights anomalies i.e., an unusual valve behaviour. While the supervised approach is suitable for valves with long operational history, the unsupervised approach is suitable for valves with no operational history.