Acoustic Emission technology for environmental and engineering health Monitoring of Offshore Renewable Energy

Great Western Four+ Doctoral Training Partnership

By combining the underwater acoustics knowledge of the University of Bath with the Reliability Engineering and Offshore Renewable Energy knowledge of the University of Exeter, the aim is to extend the remit of acoustic emission monitoring beyond the environmental sciences into the engineering assessment and monitoring of submerged structures.

interventions in challenging conditions. Acoustic Emission (AE) condition monitoring is routinely and successfully used for land-based devices, and this research shows how it can be used underwater. We review the acoustic signatures expected from operation and likely failure modes of MREDs, providing a basis for a generic classification system. This is illustrated with a Wave Energy Converter tested at Falmouth Bay (UK), monitored for 2 years. Underwater noise levels have been measured between 10 Hz and 32 kHz throughout this time, covering operational and inactive periods. Broadband MRED contributions to ambient noise are generally negligible. Time-frequency analyses are used to detect acoustic signatures (60 Hze5 kHz) of specific operational activities, such as the active Power Take Off, and relate them to engineering and environmental conditions. These first results demonstrate the feasibility of using underwater Acoustic Emissions to monitor the health and performance of MREDs. Mooring ropes are essential components of offshore installations, and synthetic ropes are increasingly preferred because of their favourable cost to weight ratios. In-service condition of these materials is traditionally monitored through costly visual inspection, which adds to the operating costs of these structures. Acoustic Emissions (AE) are widely used for condition-monitoring in air, and show great potential underwater. This research investigates the AE signatures of synthetic mooring ropes subjected to sinusoidal tension-tension loading in a controlled environment, using a large-scale dynamic tensile test rig. With a linear array of 3 broadband (20 Hz to 50 kHz) hydrophones, four main signatures are identified: low-to high frequency, low-amplitude signals (50 Hz to 10 kHz), low-amplitude broadband signals (10 kHz – to 20 kHz), high amplitude signals (10 Hz – to 48 kHz) and medium-amplitude signals (500 Hz – to 48 kHz). These AE types are related to different stages of rope behaviour, from bedding-in to degradation and failure. The main findings are that the failure location and breaking load can be identified through the detection of AE. The occurrence of high amplitude AE bursts in relation to the applied tensile load allows the detection of an imminent failure, i.e. prior to the failure event. These initial results indicate that AE analyses can enable the integrity of synthetic mooring ropes to be monitored. Marine Renewable Energy (MRE) has progressed towards commercialisation over the recent years but significant barriers still exist. This includes the currently high cost of energy, leaving MRE uncompetitive with respect to other more established renewable energy technologies. A significant proportion of this cost comes from Operation and Maintenance (O&M) activities. O&M activity can be reduced through the use of condition-based maintenance scheduling. In offshore environments, the submerged location of most devices enables the use of underwater Acoustic Emission (AE), a new condition-monitoring technique. It combines acoustics (used for environmental monitoring of MRE influence on noise levels) with AE condition monitoring as used in air. This research assesses the practicality of such an approach in complex ocean environments through detailed sound propagation modelling using the propagation model Bellhop in the Matlab toolbox AcTUP. Results show that acoustic propagation is very sensitive to variations in the shallow water environments considered. When concerning sensor placement, multiple-path interferences mean that the location of the measuring sensor(s) needs to be carefully considered, but might not cover all environmental variations over the several months necessary for accurate long-term monitoring. Associated to the shallow depths, these environmental variations also mean that some frequencies cannot be back-propagated easily, generally limiting access to the monitoring of Received Levels. The results presented here are the first steps toward optimizing AE sensor posi-tions and AE measuring strategies for arrays of devices.