A feasibility study of wind turbine blade surface crack detection using an optical inspection method

Zhang, Huiyi; Jackman, John

doi:10.1109/icrera.2013.6749869

Cited by 8 publications

(1 citation statement)

References 5 publications

(4 reference statements)

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“…The three stage crack detection methodology includes: (1) a line detection method to quickly scan a WTB and locate crack regions, (2) an edge detection method that produces a detailed representation of a crack, and (3) a crack quantification method that characterizes the severity of a crack (e.g., size, color) [12]. A series of synthetic cracks were created to control the common characteristics of surface cracks so that we could study the factors that affect the visibility of a crack.…”

Section: Methodsmentioning

confidence: 99%

Feasibility of Automatic Detection of Surface Cracks in Wind Turbine Blades

Zhang

Jackman

2014

Wind Engineering

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Cracks on the surface of a wind turbine blade (WTB) can be a sign of current or future damage to the underlying structure depending on the severity of the cracks. We investigated a new method for automatically detecting surface cracks based on image processing techniques. The method was evaluated by varying crack parameters and our method parameters. Identifying and quantifying cracks as small as hair thickness is possible with this technique. Orientation of a crack did not affect the results. The effects of uneven background illumination (present in images captured on-tower) were significantly reduced by optimizing the threshold value for the Canny edge detection method. The accuracy of quantifying a crack was increased by processing an image with both the Sobel and Canny edge detection methods and then combining the results to reduce background noise. ABSTRACTCracks on the surface of a wind turbine blade (WTB) can be a sign of current or future damage to the underlying structure depending on the severity of the cracks. We investigated a new method for automatically detecting surface cracks based on image processing techniques. The method was evaluated by varying crack parameters and our method parameters. Identifying and quantifying cracks as small as hair thickness is possible with this technique. Orientation of a crack did not affect the results. The effects of uneven background illumination (present in images captured on-tower) were significantly reduced by optimizing the threshold value for the Canny edge detection method. The accuracy of quantifying a crack was increased by processing an image with both the Sobel and Canny edge detection methods and then combining the results to reduce background noise.

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Section: Methodsmentioning

confidence: 99%