Volume 45 Issue 7
Jul.  2023
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WANG Kai, PEI Xiao-dong, YANG Tao, CHEN Rui-ding, HAO Hai-qing, JIANG Shu-guang, SUN Yong. Study on intelligent ventilation linkage control theory and supply–demand matching experiment in mines[J]. Chinese Journal of Engineering, 2023, 45(7): 1214-1224. DOI: 10.13374/j.issn2095-9389.2022.05.05.003
Citation: WANG Kai, PEI Xiao-dong, YANG Tao, CHEN Rui-ding, HAO Hai-qing, JIANG Shu-guang, SUN Yong. Study on intelligent ventilation linkage control theory and supply–demand matching experiment in mines[J]. Chinese Journal of Engineering, 2023, 45(7): 1214-1224. DOI: 10.13374/j.issn2095-9389.2022.05.05.003
shu

Study on intelligent ventilation linkage control theory and supply–demand matching experiment in mines

  • 1.

    State Key Laboratory of Coal Mine Safety Technology, China Coal Technology & Engineering Group Shenyang Research Institute, Shenyang 113122, China

  • 2.

    School of Safety Engineering, China University of Mining & Technology, Xuzhou 221116, China

  • 3.

    School of School of Mine Safety, North China Institute of Science and Technology, Langfang 065201, China

More Information
  • Corresponding author:

    YANG Tao, E-mail: yaotang585@163.com

  • Received Date: May 04, 2022
  • Available Online: August 28, 2022
  • Published Date: July 24, 2023
    Graphical Abstract
    • Abstract
  • To determine the dynamic matching of a mine ventilation system to onsite demands of automatic adjustment, we analyze the principle of air volume supply and demand matching and a linkage control method. Subsequently, we establish a mathematical model of main ventilator frequency adjustment, associate branch resistance adjustment, and joint adjustment with multi-feature fusion. We also propose a matching regulation model and a stability determination method for a ventilation network’s branch supply and demand. Based on the monitoring of harmful gases, intelligent emergency control software is developed by a mine ventilation supply and demand model. We realize the automatic calculation of the best working frequency of a ventilator when an unbalanced supply and ventilation demand is selected for frequency conversion adjustment. When selecting the associated branch wind resistance adjustment, we use a cellular automata model to calculate the optimal adjustment roadway. We obtain the adjusted wind resistance value using a winding network inversion calculation model. When a single adjustment method fails, a joint control scheme of fan frequency conversion and branch resistance adjustment is generated. A reliable adjustment of air volume supply and demand matching is realized through an advanced simulation analysis of the air network. A typical mine ventilation system is used to establish an experimental model for the automatic adjustment of the air demand of a branch of a winding network. The air demand adjustment and dilution experiment are carried out with the statistical law of onsite gas overrun as the guidance model of branch air demand control. The following results are obtained. The branch air volume changes according to the adjustment theory model under three adjustment methods. Further, the CO2 concentration change is evidently delayed in the air adjustment process. In the process of fan frequency conversion regulation, the air volume of each branch of the air network changes according to the ventilation network sensitivity, and the fluctuation of the air network is minimal. When a single associated branch resistance adjustment method is used to regulate the wind, the local wind network has great influence on air volume and thus fluctuates greatly. When the fan frequency and associated branch wind resistance are combined, the fluctuation of the branch air volume of the entire air network is the largest, and the system stability and security are the lowest. Therefore, the fan frequency and combined regulation methods of multiple associated branches are recommended to use in practical applications of mines. The experiment verified the practicability and feasibility of the deviation of mine ventilation supply and demand from intelligent control systems. It also provided theoretical and application guidance for mine ventilation linkage control.
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