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

Abstract

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.