首页> 外文期刊>Image Processing, IET >Detection and analysis of large-scale WT blade surface cracks based on UAV-taken images
【24h】

Detection and analysis of large-scale WT blade surface cracks based on UAV-taken images

机译:基于无人机图像的大型WT叶片表面裂纹检测与分析

获取原文
获取原文并翻译 | 示例

摘要

Aiming at the high cost and the poor working environment of the detection of large-scale wind turbine (WT) cracks, an analytic detection method based on blade images taken by unmanned aerial vehicles (UAVs) is proposed in this study. For the characteristics of the UAV shooting and the location of the WT, the pre-processing of motion blurring, image noise reduction and image enhancement is used to make the target area and crack details more clear and complete. Then, a crack analysis method based on the grey-scale value is proposed, taking into account the distribution, severity and development trend of the cracks, so that the blind area in the daily detection of the WT can be reduced, the subsequent maintenance of the WT blade is made more accurate, and essentially the operation and maintenance costs be reduced considerably.
机译:针对大型风轮机裂纹检测的高成本和恶劣的工作环境,提出了一种基于无人机图像的图像分析检测方法。针对无人机射击的特点和WT的位置,使用运动模糊,图像降噪和图像增强的预处理来使目标区域和裂纹细节更加清晰和完整。然后,提出了一种基于灰度值的裂纹分析方法,考虑了裂纹的分布,严重程度和发展趋势,从而减少了WT日常检测中的盲区,后续维护WT刀片更加精确,从本质上降低了运营和维护成本。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号