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Damage Detection Based on Static Strain Responses Using FBG in a Wind Turbine Blade

机译:基于FBG的风力机叶片静态应变响应损伤识别。

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摘要

The damage detection of a wind turbine blade enables better operation of the turbines, and provides an early alert to the destroyed events of the blade in order to avoid catastrophic losses. A new non-baseline damage detection method based on the Fiber Bragg grating (FBG) in a wind turbine blade is developed in this paper. Firstly, the Chi-square distribution is proven to be an effective damage-sensitive feature which is adopted as the individual information source for the local decision. In order to obtain the global and optimal decision for the damage detection, the feature information fusion (FIF) method is proposed to fuse and optimize information in above individual information sources, and the damage is detected accurately through of the global decision. Then a 13.2 m wind turbine blade with the distributed strain sensor system is adopted to describe the feasibility of the proposed method, and the strain energy method (SEM) is used to describe the advantage of the proposed method. Finally results show that the proposed method can deliver encouraging results of the damage detection in the wind turbine blade.
机译:风力涡轮机叶片的损坏检测能够使涡轮机更好地运行,并为叶片的损坏事件提供早期警报,以避免灾难性损失。本文提出了一种基于光纤布拉格光栅(FBG)的风力涡轮机叶片非基线损伤检测方法。首先,卡方分布被证明是一种有效的损伤敏感特征,被用作当地决策的单独信息源。为了获得损伤检测的全局最优决策,提出了特征信息融合(FIF)方法,对上述各个信息源中的信息进行融合和优化,并通过全局决策准确地检测出损伤。然后,采用13.2 m的带有分布式应变传感器系统的风力涡轮机叶片来描述该方法的可行性,并使用应变能法(SEM)来描述该方法的优点。最终结果表明,该方法可以为风机叶片的损伤检测提供令人鼓舞的结果。

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