Computer vision-based conveyor belt runout detection method
In the process of coal conveying,the safe and stable operation of the conveyor belt is crucial,and if the deflection fault can not be dealt with in time,it will cause more serious accidents.In order to carry out more accurate runout detection of conveyor belt,a real-time detection method of conveyor belt runout is proposed using computer vision technology.Firstly,the improved Canny operator is used to extract the edge contour information of the conveyor belt image;then the improved cumulative probability Hough transform is used to extract the straight line features of the conveyor belt edge;finally,the de-viation of the center position of the conveyor belt from the standard position and the deviation of the edge angle of the two sides of the conveyor belt from the standard angle are used to determine whether the conveyor belt is running out of line and to classify the level of running out of line.The experimental results show that the proposed conveyor belt deviation detection method can accurately calculate the center position of the conveyor belt and the edge angle of both sides of the conveyor belt,and the algorithm is effective.
conveyor belt deflectionCanny operatoradaptive thresholdHough transform
万方数据
维普
