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Belt vision localization algorithm based on machine vision and belt conveyor deviation detection

机译:基于机器视觉和带式输送机偏差检测的皮带视觉定位算法

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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.
机译:皮带输送机是工业智能的一个组成部分,但皮带输送机经常在运行过程中存在带偏转的问题。这将影响带式输送机的正常操作,因此有必要检测带式输送机的偏差。它与传统工业中使用的机械偏差检测装置不同。本文介绍了一种基于机器视觉的带式输送机偏差检测方法。提出了一种基于贲门算子和形态处理的改进的边缘检测算法及基于霍夫线检测的皮带定位算法。该算法可以适应复杂背景下的皮带定位,并且还解决了皮带边缘难以提取的直线的问题。从而实现了更好的实际检测效果。它有效解决了无法检测到传统机械接触偏差检测装置和在偏差的早期阶段预警的问题。

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