A motion-blurred restoration method for surface damage detection of wind turbine blades

Du Ying*, Hongkun Wu, David Garcia Cava

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

In order to reduce expensive cost and downtimes, visual inspection method based on unmanned aerial vehicles has become a promising method for surface damage detection in wind turbine blades. Due to the fact that the linear velocity of points on the blade varies along its longitudinal dimension while the blade is in-operation, the captured blade image suers degradation caused by motionblur, and the degradation process of the image is nonlinear. To address this issue, an area-based deblurring method is rstly developed. The points on each divided region can be assumed to follow a uniform motion with the same linear velocity and blurring eect, which indicates that the nonlinear problem can be resolved by linear methods. Point spread function estimation is then conducted to each region to obtain the blur kernels, and image restoration of each region is carried out by using Wiener lter algorithm. Ultimately, image fusion is implemented to merge all the restored regions to realize blade image restoration. Experimental results and evaluation have demonstrated that the proposed areabased method can mitigate blurring effects of rotating blade images, thus further improve the detection accuracy for the on-line inspection.
Original languageEnglish
Article number113031
Early online date16 May 2023
Publication statusPublished - Aug 2023

Keywords / Materials (for Non-textual outputs)

  • Wind turbine blades
  • Vision-based monitoring
  • Motion-blur estimation
  • Image restoration
  • Surface damage detection


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