个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:土木工程系
电子邮箱:renliang@dlut.edu.cn
A review of damage detection methods for wind turbine blades
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论文类型:期刊论文
发表时间:2015-03-01
发表刊物:SMART MATERIALS AND STRUCTURES
收录刊物:SCIE、EI
卷号:24
期号:3
ISSN号:0964-1726
关键字:turbine blade; damage detection; structural health monitoring; wind energy
摘要:Wind energy is one of the most important renewable energy sources and many countries are predicted to increase wind energy portion of their whole national energy supply to about twenty percent in the next decade. One potential obstacle in the use of wind turbines to harvest wind energy is the maintenance of the wind turbine blades. The blades are a crucial and costly part of a wind turbine and over their service life can suffer from factors such as material degradation and fatigue, which can limit their effectiveness and safety. Thus, the ability to detect damage in wind turbine blades is of great significance for planning maintenance and continued operation of the wind turbine. This paper presents a review of recent research and development in the field of damage detection for wind turbine blades. Specifically, this paper reviews frequently employed sensors including fiber optic and piezoelectric sensors, and four promising damage detection methods, namely, transmittance function, wave propagation, impedance and vibration based methods. As a note towards the future development trend for wind turbine sensing systems, the necessity for wireless sensing and energy harvesting is briefly presented. Finally, existing problems and promising research efforts for online damage detection of turbine blades are discussed.