Acoustic Emission Technology for Engineering Health Monitoring of a Wave Energy Converter
Date: 11 February 2019
University of Exeter
PhD in Renewable Energy
Marine renewable energy has the potential to produce up to 20% of the UK’s current electricity demand, leading to extensive research and development activities in this area. As the industry of wave energy progresses toward commercialisation, a number of barriers still limit its potential, including the cost of energy. A significant ...
Marine renewable energy has the potential to produce up to 20% of the UK’s current electricity demand, leading to extensive research and development activities in this area. As the industry of wave energy progresses toward commercialisation, a number of barriers still limit its potential, including the cost of energy. A significant portion of this is the cost of operation and maintenance activity due to the challenging environments in which wave energy devices reside. Maintenance activity as it stands can include vessel activity and skilled workers including divers. Condition monitoring techniques designed for the wave energy industry and utilising the water that surrounds the devices could reduce maintenance costs by decreasing human intervention and the early detection of faults and degradation. This thesis looks to explore the feasibility of underwater Acoustic Emission (AE) monitoring as a method of condition-based maintenance for wave energy converters and other marine energy devices. This is achieved through three strands of work: sea trials, component testing and propagation modelling. Eighteen months of acoustic data from the Lifesaver wave energy converter, deployed at Falmouth Bay Test Facility in Falmouth Bay, UK, are re-assessed for evidence of component AE signatures. Signatures are identified and presented from the power-take-off and generator of the device. Novel testing is conducted through submerged marine component testing adapted to include AE monitoring. Three 12-strand double braided synthetic mooring ropes undergo cyclic fatigue testing and AE signals detected can be classified by amplitude and frequency range, with increasing severity as the component loading is increased before sample failure. Finally, propagation modelling is used to understand the effect of AE from engineering components on the local soundscape. To enable a comparison between devices, a new efficiency ratio is presented that compares the underwater acoustic energy emitted through the life cycle of the wave energy converter to the useful electrical energy produced by the device. This thesis presents the first steps toward a novel method of condition monitoring in an ocean environment, potentially adaptable for arrays of devices.
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