Study on the collaborative intelligent control system of airflow and spray for dust-reduction in gas-solid-liquid coupling environment - Chen, Long; Gong, Xiaoyan; Xue, Yuxuan; Fu, Haoran; Liu, Zhuangzhuang; Wang, Xinyu; Fei, Yinghao (Powder technology, 2025)
The development of full-face rapid excavation technology in the fully-mechanized excavation face of coal mines has significantly enhanced excavation efficiency but also increased dust production. Traditional dust control methods, such as extensive ventilation and spray reduction, fail to adjust dynamically and precisely to actual conditions, leading to ineffective dust control. Based on the migration mechanisms of the flow field within a complex ventilation environment characterized by airflow-dust-droplet interactions, we developed a collaborative intelligent control system that dynamically adjusts airflow direction, velocity, spray pressure, and nozzle diameter, effectively managing and reducing dust levels. Utilizing Fluent-EDEM technology, we validated a transient calculation model through gas-solid-liquid coupling simulations and underground trials. This model enabled us to analyze the impact of parameter variations on dust distribution at critical locations, including the breathing zones of drivers and miners in airflow return side. A dual-objective optimization model and parametric software has been established for dust field management using the Pareto method and response surface methodology. We employed case trials on the fully-mechanized excavation face of a coal mine in northern Shaanxi by designing and constructing the experimental platform. Under different working conditions, the dust concentration with the best collaborative control scheme has been tested, and compared with the calculated value of the optimization model, the absolute value of the maximum relative error is 11.2 %. Notably, in extreme conditions with a 10 m distance from the air vent to the face, the dust concentration in the miners' breathing zone on the return airflow side was reduced by 75.5 % from 374.96 mg/m3 to 91.81 mg/m3, and the dust concentration at the driver's position was reduced by 41.8 % from 449.53 mg/m3 to 261.73 mg/m3. These in-field results validate both the system and model's accuracy and effectiveness. [Display omitted] •Dust-reduction by the collaborative intelligent control of airflow and spray.•A gas-solid-liquid coupling simulation transient model using the JKR collision model.•A dual-objective dust field optimization model established to solve optimal schemes.