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Feasibility of a fully autonomous wireless monitoring system for a wind turbine blade

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journal contribution
posted on 03.06.2016 by Ozak Esu, Steve Lloyd, James Flint, Simon Watson
Condition monitoring (CM) of wind turbine blades has significant benefits for wind farm operators and insurers alike. Blades present a particular challenge in terms of operations and maintenance: the wide range of materials used in their construction makes it difficult to predict lifetimes; loading is stochastic and highly variable; and access can be problematic due to the remote locations where turbines are frequently located, particularly for offshore installations. Whilst previous works have indicated that Micro Electromechanical Systems (MEMS) accelerometers are viable devices for measuring the vibrations from which diagnostic information can be derived, thus far there has been no analysis of how such a system would be powered. This paper considers the power requirement of a self-powered blade-tip autonomous system and how those requirements can be met. The radio link budget is derived for the system and the average power requirement assessed. Following this, energy harvesting methods such as photovoltaics, vibration, thermal and radio frequency (RF) are explored. Energy storage techniques and energy regulation for the autonomous system are assessed along with their relative merits. It is concluded that vibration (piezoelectric) energy harvesting combined with lithium-ion batteries are suitable selections for such a system.



  • Mechanical, Electrical and Manufacturing Engineering

Published in

Renewable Energy


ESU, O.O. ...et al., 2016. Feasibility of a fully autonomous wireless monitoring system for a wind turbine blade. Renewable Energy, 97, pp. 89–96.


© The Authors. Published by Elsevier


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This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

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This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/