Automatic Detection Method for Excessive Swing of the Upper Guide Shaft of Hydroelectric Generator Based on Machine Vision
Aiming at the problems of low detection accuracy in existing methods,a machine vision based automatic detection method for excessive swing of the upper guide shaft of a hydroelectric generator is proposed.First,obtain the image,use Laplace operator for image edge detection,and calculate the frequency of grayscale values in the grayscale image.Then,feature matching algorithms are used to extract key feature points from the pendulum image,and the Hough transform is used to map the straight line features of the guide axis image on the water turbine to a two-dimensional image space,transforming the straight line features into points in the parameter space.Finally,set the threshold for the actual swing process,and compare the calculated swing value with the threshold to determine whether the swing exceeds the limit.The results show that the error between the actual value obtained from 10 tests and the measured value is between 0～0.1mm,which meets the expected accuracy requirements for swing measurement in actual production and has a good application effect.
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