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首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >3D RECONSTRUCTION OF ON-/OFFSHORE WIND TURBINES FOR MANUAL AND COMPUTATIONAL VISUAL INSPECTION
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3D RECONSTRUCTION OF ON-/OFFSHORE WIND TURBINES FOR MANUAL AND COMPUTATIONAL VISUAL INSPECTION

机译:用于手动和计算视觉检查的/海上风力涡轮机的三维重构

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摘要

The expansion of off-/onshore wind farms plays a key role in the transformation of energy production from burning of fossil fuels and nuclear energy to sustainable and safe power generation. However, the wind energy sector is permanently under strong cost pressure and the maintenance of the turbines is currently still carried out quite expensively with human industrial climbers. In this article, we present the results of an interdisciplinary research project on the automation of various image-based inspection steps. Since the use of unmanned aerial vehicles (UAV) is a problem especially offshore, we present here a simple, cost-effective method to obtain a three-dimensional model of a wind energy plant using solely a digital camera equipped with a sensor array to use it for the detection and management of damages and abnormalities. A first approach to detect abnormalities on the surface with deep learning methods achieved an F1-score of about 95%.
机译:off-/陆上风电场的扩展在能源生产转变中发挥着关键作用,从化石燃料和核能燃烧到可持续和安全的发电。然而,风能部门永久性地承受强劲的成本压力,目前仍然与人工工业登山者相当地进行涡轮机的维护。在本文中,我们介绍了对各种基于图像的检查步骤的自动化跨学科研究项目的结果。由于使用无人驾驶飞行器(UAV)是一个尤其是近海问题,我们在这里介绍了一种简单,经济有效的方法,可以使用单独配备有传感器阵列的数码相机来获得风能设备的三维模型。它用于检测和管理损害和异常。一种检测表面异常的方法,具有深度学习方法的F1分数约为95%。

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