Abstract
Belt conveyors are an integral part of industrial intelligence, but belt conveyors often have problems with belt deflection during operation. This will affect the normal operation of the belt conveyor, so it is necessary to detect the deviation of the belt conveyor. It is different from the mechanical deviation detection device used in traditional industries. This paper presents a machine vision based belt conveyor deviation detection method. An improved edge detection algorithm based on Canny operator and morphology processing and a belt positioning algorithm based on Hough line detection are proposed. The algorithm can adapt to the belt positioning under complex background, and also solves the problem that the straight line of the belt edge is difficult to extract. Thereby achieving a better actual detection effect. It effectively solves the problem that the traditional mechanical contact deviation detection device can not be detected and early warning in the early stage of the deviation.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call