Current Search: Bowren, Mark. (x)
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Title
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Software framework for prognostic health monitoring of ocean-based power generation.
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Creator
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Bowren, Mark., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
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Abstract/Description
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On August 5, 2010 the U.S. Department of Energy (DOE) has designated the Center for Ocean Energy Technology (COET) at Florida Atlantic University (FAU) as a national center for ocean energy research and development of prototypes for open-ocean power generation. Maintenance on ocean-based machinery can be very costly. To avoid unnecessary maintenance it is necessary to monitor the condition of each machine in order to predict problems. This kind of prognostic health monitoring (PHM) requires a...
Show moreOn August 5, 2010 the U.S. Department of Energy (DOE) has designated the Center for Ocean Energy Technology (COET) at Florida Atlantic University (FAU) as a national center for ocean energy research and development of prototypes for open-ocean power generation. Maintenance on ocean-based machinery can be very costly. To avoid unnecessary maintenance it is necessary to monitor the condition of each machine in order to predict problems. This kind of prognostic health monitoring (PHM) requires a condition-based maintenance (CBM) system that supports diagnostic and prognostic analysis of large amounts of data. Research in this field led to the creation of ISO13374 and the development of a standard open-architecture for machine condition monitoring. This thesis explores an implementation of such a system for ocean-based machinery using this framework and current open-standard technologies.
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Date Issued
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2012
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PURL
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http://purl.flvc.org/FAU/3342035
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Subject Headings
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Machinery, Monitoring, Marine turbines, Mathematical models, Fluid dynamics, Structural dynamics
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Format
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Document (PDF)
