Abstract
Conveying systems are responsible for a large part of continuous horizontal transportation in underground mines. The total length of a conveyor network can reach hundreds of kilometers, while a single conveyor usually has a route length of about 0.5–2 km. The belt is a critical and one of the most costly components of the conveyor, and damage to it can result in long unexpected stoppages of production. This is why proper monitoring of conveyor belts is crucial for continuous operation. In this article, algorithms for the detection of potential damage to a conveyor belt are described. The algorithms for analysis used video recordings of a moving belt conveyor, which, in case the of hazardous conditions of deep mines, can be collected, for example, by a legged autonomous inspection robot. The video was then analyzed frame by frame. In this article, algorithms for edge damage detection, belt deviation, and conveyor load estimation are described. The main goal of the research was to find a potential application for image recognition to detect damage to conveyor belts in mines.
Highlights
The proposed methods were mainly based on the edge detection of objects present on the frame
The speed of the conveyor belt, the length of the conveyor, and their quantity made it difficult to monitor them in real time with the naked eye
Their failure may result in interruptions in the entire production as they other facilities
Summary
The availability of ready-to-use machines throughout industry is one of the main factors influencing effective production and ensuring its continuity For this reason, the technical condition of infrastructure elements is regularly inspected. The length of a single conveyor usually fluctuates from several hundred meters to several kilometers (depending on the place and destination) Due to their role in the production process, their work should be undisturbed and uninterrupted. For the automatic detection of belt defects, the solutions used are based on magnetic signals, RGB, and thermal images These are usually portable measuring devices supporting inspection works [2,3,4]. Our approach involved the use of an UGV that would constantly monitor the belt condition of conveyors, in particular by searching for belt deviation and torn edges with the use of a camera and machine vision techniques.
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