GONG Xiaoyan, PENG Gaogao, SONG Tao, FENG Xiong, CHEN Fei, LIU Hui, XIE Pei, XUE He. Study on air flow control parameters of long-pressure and short-extraction ventilation air outlets in heading face[J]. Journal of Mine Automation, 2021, 47(9): 45-52.. DOI: 10.13272/j.issn.1671-251x.2021060008
Citation: GONG Xiaoyan, PENG Gaogao, SONG Tao, FENG Xiong, CHEN Fei, LIU Hui, XIE Pei, XUE He. Study on air flow control parameters of long-pressure and short-extraction ventilation air outlets in heading face[J]. Journal of Mine Automation, 2021, 47(9): 45-52.. DOI: 10.13272/j.issn.1671-251x.2021060008

Study on air flow control parameters of long-pressure and short-extraction ventilation air outlets in heading face

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  • Published Date: September 19, 2021
  • The air flow at the air outlet cannot be dynamically adjusted according to the actual needs of the tunneling process under the long-pressure and short-extraction ventilation mode of the heading face, resulting in unreasonable air flow distribution and serious dust accumulation. The existing studies on the air flow distribution and dust reduction effect of long-pressure and short-extraction ventilation outlet at the heading face are only single analyses of the effect of the change of the air duct air outlet parameters on the air flow distribution and dust reduction effect in the heading face, without considering the interactive effect of each parameter on the dust field migration distribution. Moreover, there is no in-depth research on how the parameters of the air outlet can be changed comprehensively to achieve the optimal ventilation and dust reduction effect in different tunneling stages. In order to solve the above problems, taking the S1204 heading face of Shenmu Ningtiaota Mine in Yulin, Shaanxi Province as the research object, a finite element model of air flow control with variable air outlet parameters is established. The effect of the change of air duct air outlet parameters on the air flow and dust concentration migration distribution is simulated and analyzed. Through numerical analysis, the air outlet diameter, horizontal right deviation angle and vertical up deviation angle of the air duct are selected as the air flow dynamic control parameters of the air outlet, and the air speed and dust concentration data of the driver position and the pedestrian position on the return air side after the adjustment of different air flow control parameters are extracted. Through the niche genetic algorithm, the extracted air flow control data are mined and analyzed with the lowest dust concentration at the driver position and the pedestrian position on the return air side as the optimization object. And the optimal air flow control parameters are obtained for the closest distance of 5 m and the farthest distance of 10 m between the air outlet of S1204 heading face and the driving end face. At 5 m, the air outlet diameter is 1.1-1.2 m, the horizontal right deviation angle is 10-15°, and the vertical up deviation angle is 3-6°. At 10 m, the air outlet diameter is 0.8-0.9 m, the horizontal right deviation angle is 0-5° and vertical up deviation angle is 0-3°. A 1∶5 similar simulation test platform for intelligent control of air flow of the heading face of S1204 is built, and the optimal air flow control parameters are tested and analyzed. The results show that the dust concentration at the driver position is reduced by up to 52.3%, and the dust concentration at pedestrian position on the return air side is reduced by up to 60.6%, which verifies the accuracy of the optimal air flow control parameters.
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