复合材料科学与工程 ›› 2020, Vol. 0 ›› Issue (9): 85-89.

• 应用研究 • 上一篇    下一篇

基于无人机的风机叶片缺陷自动检测技术

毛希玮, 徐莹莹   

  1. 国家电投集团江苏新能源有限公司,南京210009
  • 收稿日期:2019-12-18 出版日期:2020-09-25 发布日期:2020-09-28
  • 作者简介:毛希玮(1969-),男,工程师,主要从事新能源项目(风电、光伏)开发和运营工作方面的研究,1782815993@qq.com。

AUTOMATIC DEFECT DETECTION OF WIND BLADE SURFACE VIA UAV

MAO Xi-wei, XU Ying-ying   

  1. Spic Jiangsu Electric Power Co., Ltd., Nanjing 210009, China
  • Received:2019-12-18 Online:2020-09-25 Published:2020-09-28

摘要: 随着我国风力发电产业的迅速发展,风电机组容量不断扩展,风机叶片长度增加,叶片发生损伤的概率也随之变大,因此对风机叶片进行状态监测和缺陷识别至关重要。因为目前用于检测风机叶片的传统方法费时费力且成本高,所以本研究提出了一种基于无人机(Unmanned Aerial Vehicle,UAV)与图像处理(Image processing)技术相结合的方法,推动风机叶片检测朝着自动化、快速化、低成本的方向发展。利用实际场景下采集的风机叶片图像进行自动化缺陷检测实验,实验结果验证了算法的有效性、可靠性和准确性,能较好地满足对风机叶片缺陷的检测要求。

关键词: 风机叶片, 缺陷检测, 无人机, 图像处理, 复合材料

Abstract: With the rapid development of industrialization for wind power electricity generation, the continuous expansion of wind turbine capacity, the length of wind turbine blades is increasing, and the probability of blade damages is also increasing. Therefore, it is very urgent and important to monitor the condition of the wind turbine blade and detect the defect. As the traditional methods used for detecting the wind turbine blades are time-consuming, laborious and costly, this study proposed a new method based on Unmanned Aerial Vehicle (UAV) and image processing technologies to achieve the wind blade inspection rapidly, automatically and low-costly. An experiment is carried out to test the defect detection performance of the proposed method by using the wind turbine blade images collected in real situations. Furthermore, the experimental results show that the presented algorithm is effectiveness, reliability and accuracy, which can basically meet the requirements of blade defect detection, and is of great significance in practical engineering.

Key words: wind turbine blade, defect detection, UAV, image processing, composites

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