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Health monitoring of wind turbine blades in operation using three-dimensional digital image correlation

机译:使用三维数字图像关联对运行中的风力涡轮机叶片进行健康监控

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Wind turbine blades are subjected to fluctuating loads during operation, which makes them vulnerable to reduced performance and mechanical failures. In addition, the maintenance of blades is time-consuming and expensive. In this paper, a novel and economic optical technique based on three-dimensional digital image correlation (3D-DIC) is described for monitoring the health of wind turbine blades. A fault detection method is proposed based on the relative deformation of the turbine blades during operation. To validate the approach, a 5 kw wind turbine with 4 m diameter was evaluated using 3D-DIC. The rotor blades were prepared with a random black-and-white pattern of dots and two digital cameras were located in front of the wind turbine to document the rotor blade deformation. The full-field dynamic parameters of displacement and strain were obtained and a diagnosis of the blade health was conducted in both the time and frequency domains. Results showed that 3D-DIC can serve as an effective non-contact method for monitoring the health of wind turbine blades during operation. (C) 2019 Elsevier Ltd. All rights reserved.
机译:风力涡轮机叶片在运行期间会承受波动的负载,这使其容易受到性能降低和机械故障的影响。另外,叶片的维护既费时又昂贵。在本文中,描述了一种基于三维数字图像相关技术(3D-DIC)的新颖经济的光学技术,用于监测风力涡轮机叶片的健康状况。提出了一种基于运行过程中涡轮叶片相对变形的故障检测方法。为了验证该方法,使用3D-DIC对直径为4 m的5千瓦风力涡轮机进行了评估。转子叶片准备有随机的黑白图案的点,并且两个数码相机位于风力涡轮机的前面,以记录转子叶片的变形。获得了位移和应变的全场动态参数,并在时域和频域对叶片的健康状况进行了诊断。结果表明,3D-DIC可以作为一种有效的非接触式方法,用于在运行期间监测风力涡轮机叶片的健康状况。 (C)2019 Elsevier Ltd.保留所有权利。

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