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

被引:24
作者
Esu, O. O.
Lloyd, S. D. [2 ]
Flint, J. A. [1 ]
Watson, S. J. [2 ]
机构
[1] Univ Loughborough, Wolfson Sch Mech Elect & Mfg Engn, Wireless Commun Res Grp, Ashby Rd, Loughborough LE11 3TU, Leics, England
[2] Univ Loughborough, Wolfson Sch Mech Elect & Mfg Engn, Ctr Renewable Energy Syst Technol, Ashby Rd, Loughborough LE11 3TU, Leics, England
基金
英国工程与自然科学研究理事会;
关键词
Condition monitoring; Energy harvesting; Wind energy; Electromechanical sensors; Energy management; Wireless communications; STRUCTURAL DAMAGE; FREQUENCY; ALGORITHM;
D O I
10.1016/j.renene.2016.05.021
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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. (C) 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
引用
收藏
页码:89 / 96
页数:8
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