Abstract
Complex mechanical systems used in the mining industry for efficient raw materials extraction require proper maintenance. Especially in a deep underground mine, the regular inspection of machines operating in extremely harsh conditions is challenging, thus, monitoring systems and autonomous inspection robots are becoming more and more popular. In the paper, it is proposed to use a mobile unmanned ground vehicle (UGV) platform equipped with various data acquisition systems for supporting inspection procedures. Although maintenance staff with appropriate experience are able to identify problems almost immediately, due to mentioned harsh conditions such as temperature, humidity, poisonous gas risk, etc., their presence in dangerous areas is limited. Thus, it is recommended to use inspection robots collecting data and appropriate algorithms for their processing. In this paper, the authors propose red-green-blue (RGB) and infrared (IR) image fusion to detect overheated idlers. An original procedure for image processing is proposed, that exploits some characteristic features of conveyors to pre-process the RGB image to minimize non-informative components in the pictures collected by the robot. Then, the authors use this result for IR image processing to improve SNR and finally detect hot spots in IR image. The experiments have been performed on real conveyors operating in industrial conditions.
Highlights
Belt conveyors are used to transport bulk materials over long distances
All frames were taken during the simulated robot inspection, where the robot was constantly moving along the belt conveyor
A procedure for image processing and information fusion based on datasets acquired during belt conveyor inspection was proposed in this paper
Summary
Belt conveyors are used to transport bulk materials over long distances. Due to the harsh environmental conditions, the elements of the conveyor are subject to accelerated degradation processes and must be monitored. One of the key problems is monitoring the degradation of thousands of idlers installed to support the belt. High humidity, impulsive load (when oversized pieces of material on the belt pass the idler), temporal overloading, etc., may cause really accelerated degradation of the coating of the idler and rolling element bearings installed inside the idler in order to give the rolling ability. One of the most popular ways to evaluate the condition of the idler is its visual inspection, temperature measurement, and acoustic sound analysis. We propose to use both RGB images and IR images from infrared cameras
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