Abstract
Aiming at the shortcomings of the image excessively smoothing and the threshold value need to be determined in advance when the Canny algorithm is used for edge detection, an improved Canny algorithm is proposed to detect the blade chord length of the turbine generator. Selecting a proper Gaussian filter coefficient to smooth the original image and remove white noise effects while maintaining the edge information. The image gradient histogram after non-maximum suppression is processed with the Otsu method (the maximum between-class variance method) to adaptively set the high and low threshold. Using the improved canny edge detection method to detect the blade chord length and verify the modified blade. The results show that the hydrodynamic performance of the modified blade has been significantly improved, indicating that the improved canny edge detection algorithm can accurately detect the real edge of the blade, and has a strong self-adaptability. Its detection results are better than the traditional Canny algorithm.
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