Research on an Intelligent Sorting System for Foreign Matter in Coal Based on Machine Vision
2023-10-17
During coal mining, raw coal frequently becomes contaminated with various types of scrap metal, anchor bolts, anchor cables, mesh panels, damaged conveyor belts, cable terminations, timber, and other production‑related waste materials. In addition, domestic waste generated by underground operations—such as plastic bottles and plastic bags—can also find its way into the mined coal. These foreign materials in the coal readily clog pipelines, chutes, valves, screen openings, and other components, becoming one of the primary factors hindering the continuous operation of coal preparation plants. Depending on the severity, such contaminants can block conveying systems, reduce the efficiency of desliming and density‑separation units, and lead to spillage, leakage, or dripping; in more serious cases, they may cause scratches on belt conveyors or block sorting equipment, resulting in equipment failures and product‑quality incidents. If these impurities enter the marketable coal, their presence during end‑use could damage operating machinery, trigger boiler explosions, or give rise to other safety‑related accidents, inflicting substantial economic losses and even causing casualties. Moreover, the presence of foreign matter constrains the development of coal export business, often giving rise to unnecessary commercial disputes and claims, thereby imposing unwarranted financial losses on coal producers.
Removing foreign matter from coal is both a longstanding and an emerging challenge. Both coal producers and end‑users have consistently prioritized the sorting of impurities in coal. In recent years, this issue has grown increasingly pressing, with ever‑stricter demands for sorting efficiency. The traditional “three‑suction‑one‑screen” method, with its low throughput, can no longer meet the growing need to eliminate a wide range of contaminants from coal.
At present, a multi‑stage iron‑removal approach employing electromagnetic separators has proven highly effective for eliminating metallic contaminants. As for woody debris in coal, both domestically and internationally, the prevailing practice is to integrate crushing and screening stages into the processing flow to facilitate separation; alternative methods include using water‑based vertical‑wheel classifiers, inclined‑wheel classifiers, or trough classifiers to remove wood chips. Overall, these techniques deliver some degree of efficacy, yet each also exhibits certain limitations. Mechanical devices such as debris‑blocking screens and debris‑removal hooks have likewise become common in recent years; however, their removal efficiency is relatively low, and they require frequent inspection and maintenance, resulting in significant operational constraints.
To reduce the amount of foreign matter in commercial coal, most coal preparation plants typically incorporate a manual sorting stage on the lump‑coal hand‑sorting belt conveyor to remove impurities. However, this approach suffers from low impurity removal rates, high labor intensity for workers, and reduced safety levels.
Based on the current status of debris‑separation equipment in use in China, low efficiency, frequent malfunctions, and extensive maintenance requirements are the primary factors hindering the widespread adoption of such systems. To mitigate the adverse impact of extraneous materials on coal production, and in response to the complex and heterogeneous nature of these contaminants, an intelligent debris‑sorting system—based on machine vision for automated identification and equipped with a robotic arm for precise grasping—has been developed. This system, hereafter referred to as the “Intelligent Debris‑Sorting System,” has been successfully implemented at the Wobei Coal Preparation Plant of Huaibei Mining Group.
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