Research on a system for the diagnosis and localization of conveyor belt deviations in belt conveyors

Abstract

To address the shortcomings of existing conveyor belt deviation detection methods, such as the small detection range and slow detection speed, a method that utilizes machine vision technology to detect belt deviations in belt conveyors is proposed. A track-type inspection robot was used to collect real-time running images of a conveyor belt; Wiener filtering was carried out, grayscale processing was used, Canny edge detection, Hough transform and least squares fitting operations were used to extract the straight lines of the edges of the conveyor belt, and the offset from the straight lines of the conveyor belt under normal running conditions was calculated. To address the cumulative error problem caused by the long time and long distance in the process of locating the wheel odometer, a joint localization technology that used radio frequency identification (RFID) and a wheel odometer was proposed, and the error correction was carried out for a rotary encoder by using the RFID technology. The experimental results demonstrate that the detection method achieved a detection accuracy of over 92.1% with a detection speed of up to 31 FPS. This method enables the fast and precise identification of conveyor belt deviations, and it satisfies the requirements for real-time detection for belt conveyors. The location accuracy of the localization system that combined RFID and a wheel odometer was able to reach the centimeter level, and the system could accurately locate the positions of belt deviations. This is of vital significance for ensuring safety and efficiency in production by enterprises.