Companies Develop Monitoring Tech To Reduce Offshore Turbine Failures

Posted by Lauren Tyler on October 11, 2016 No Comments

Aquaterra Energy, which designs and delivers offshore engineering solutions, and Proeon Systems, which provides a range of turnkey safety and control system services, say they have developed a cost-saving, integrated structural monitoring system to improve the integrity of offshore wind structures.

With global offshore wind expenditure forecast to reach 210 billion British pounds over the next 10 years, the offshore wind energy monitoring system will improve inspection and repair planning and lower the frequency of offshore failures, according to the companies. It will also greatly reduce the need, risk and cost associated with inspection crews traveling to wind farm sites offshore.

The companies note that this collaboration is an amalgamation of Proeon’s sensor technology and Aquaterra’s capability in structural mechanics and analysis that will provide operators with accurate, informed and real-time condition analysis data to enhance maintenance, commissioning and decommissioning programs.

Specifically, a variety of sensors can be deployed and placed on all aspects of the installed turbine support structure, including the nacelle and foundation pile, to monitor strain, movement, temperature, scour and meteorological data. The results can then be compared against initial data collected in normal conditions and show the potential of degradation occurring.

Andrew Lennon, senior riser analyst with Aquaterra Energy, said, “Current monitoring solutions produce data but don’t provide meaningful analysis. This can lead to a lack of understanding in the industry about why failures and structural problems are occurring.

“The monitoring system mitigates the need for costly offshore inspections while providing knowledge and reassurance about the integrity of the asset. For example, where there is cracking or other problems in the structure, the data can be used to identify events [that] may be the cause. Trends in the data could be used in the future to identify problems before they occur and to determine life expectancy more accurately.”

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