Teaching experimental design of surfactant-assisted coal/gangue recognition
[Objective]The fast,accurate identification of coal and gangue is one of the essential technologies of intelligent mining,which is critical to promoting green intelligent mining of thick coal seams in China.Because the surface colors of gangue and coal are remarkably close,identification errors often arise when visible light image recognition technology is used.However,traditional infrared recognition technology cannot effectively distinguish gangue from coal owing to the small temperature difference between them.Therefore,a modern technology of"liquid intervention+infrared detection"is suggested to identify coal gangue by spraying specific types of liquid on the surface of coal and gangue.[Methods]The different temperature drop occurs on the surface of coal and gangue,that is,the area of coal and gangue in the infrared image is increased by active intervention.Then,an infrared thermal imager and an image recognition algorithm are used to distinguish coal and gangue and calculate the gangue mixing rate.Considering that surfactants can change the surface properties of coal and gangue and thus expand the temperature difference between coal and gangue,experiments on coal gangue identification with the assistance of different concentrations of surfactants based on the new technology of"liquid intervention+infrared detection"are performed.The influence of surfactants on the coal/gangue recognition effect is investigated from three aspects:coal temperature variation law,coal-gangue temperature difference law,mixed rate,and identification accuracy.[Results]The experimental results reveal the following:1)Surfactants can immensely improve the temperature variation of coal and gangue,but the extent to which diverse concentrations of surfactants enlarge the temperature variance of coal waste varies.2)DATB surfactant has the best effect on lowering coal temperature,whereas CTAB surfactant has the best influence on lowering gangue temperature.The cooling effect of anionic surfactants SDBS and SDS on coal waste is connected with their concentration,but not directly proportional.3)Compared with the clean water controlled group,the DATB solution with 0.05%concentration has the greatest short-term temperature difference enhancement on coal and gangue.At 4 s after the intervention,the temperature variance between coal and gangue increases by about 73%compared with that of clean water,and the recognition accuracy rate reaches 97.71%,which can substantially enhance the recognition accuracy rate of coal gangue based on infrared images.4)Because the temperature variance between coal and gangue is decided by the temperature drop of coal and gangue simultaneously,expanding their temperature difference needs to enhance the temperature drop of coal and weaken that of gangue.Hence,the performance of coal-gangue identification aided by surfactants can be further strengthened by merging various surfactants to fully develop the characteristics and synergistic effect of different surfactants.[Conclusions]The experimental design is based on the innovative achievements in the field of intelligent coal drawing.The experimental process entails the intersection of multiple disciplines,such as mining engineering,computer science,and chemistry,which advances the students'ability to apply interdisciplinary knowledge comprehensively to solve practical problems and is crucial for cultivating high-quality intelligent mining talents.
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