An Online Flexible Sorting Model for Coal and Gangue Based on Multi-Information Fusion

Coal is one of the most important sources in China. The separation of coal and gangue is a key link in coal mining, and its intellectualization promotes the intelligent development of coal mining. But it is difficult to sort coal and gangue quickly and accurately because of some reasons, such as fast running speed of belt, different shapes and sizes of gangue, and so on. To solve the problem, an online flexible sorting model based on multi-information fusion is proposed. We use a near-infrared camera to identify coal and gangue, and combine it with a depth camera to obtain the height and pose information of gangue. Besides, we analyze the factors that affect the trajectory of gangue before and after pneumatic separation, deduce the theoretical formula of horizontal movement distance of gangue pneumatic separation, establish the mathematical model of gangue flexible sorting, and carry out experiments of pneumatic separation with different shapes and sizes of gangue. Experimental data is used to realize error compensation of the model. Finally, experimental results verify that the gangue flexible sorting model improve the accuracy of gangue sorting effectively and sort gangue with different shapes and sizes accurately despite the high-speed movement of belt.

Abstract licence: CC BY-NC-ND

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