Defect Detection of Wind Turbine Blade Based on Unmanned Aerial Vehicle-taken Images

doi:10.12096/j.2096-4528.pgt.2018.043

Abstract

Abstract:

Aiming at the problems of inefficient manual detection of wind turbine (WT) blades and difficult diagnosis of defects, a method of defects detection for WT blades based on unmanned aerial vehicle (UAV) and image processing is proposed. Through the joint development of Halcon 12 and Visual Studio 2015, the functions of image processing flow, test result output and defects playback are realized, including camera calibration, image processing through fast adaptive weighted median filtering and dynamic threshold segmentation. Through the regional processing to identify defects such as cracks and trachoma, the defects are classified and measured, and the analysis report of WT blades quality can be output to finally realize the automatic detection function of the surface defects of the WT blades. The high accuracy and stability of the algorithm of this method in detecting WT blades surface defects are demonstrated experimentally.

Key words: wind turbine, defects detection, unmanned aerial vehicle, image processing

Zifeng QIU,Shuangxin WANG,Meng LI. Defect Detection of Wind Turbine Blade Based on Unmanned Aerial Vehicle-taken Images[J]. Power Generation Technology, 2018, 39(3): 277-285.

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