Enhancing in-situ coal-gangue identification in LTCC mining via secondary surfactant intervention and infrared thermography

Abstract

Accurate in-situ identification of coal and gangue is critical for intelligent mining, particularly in longwall top coal caving (LTCC) mining, where it enables precise control of the gangue mixed ratio and enhances resource recovery. This study introduces a Secondary Intervention strategy to augment the conventional ‘‘liquid intervention + infrared detection” approach. Results demonstrate that Secondary Intervention can consistently enhance the thermal contrast between coal and gangue, and the average accuracy of infrared image recognition for coal and gangue increased from 79.14% after the First Intervention to 93.75% after the Secondary Intervention, representing an improvement of 14.61%. Furthermore, the average contact angle difference between coal and gangue expanded from 16.64° after the First Intervention to 33.80° after the Secondary Intervention, an increase of 17.16°. Meanwhile, the area difference between coal and gangue increased by 4.94 times. Moreover, based on comprehensive analysis of the temperature difference, accuracy of morphological identification, as well as the contact angle and area of droplets, the eco-friendly compound surfactant (EFCS) of Soapnut Saponin (SS) + CTAB with a concentration of 0.06 wt% demonstrated optimal performance. These findings advance liquid intervention techniques for infrared-based recognition and support the development of greener, more intelligent coal production systems.

Keywords

Coal-gangue identification / Infrared thermography / Secondary Intervention / Longwall top coal caving (LTCC) / Intelligent mining / Heat transfer

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