基于遗传算法的保护层工作面深孔松动预裂爆破参数优化与实践

    Optimization and practice of deep hole loosening presplitting blasting parameters of protective layer working face based on genetic algorithm

    • 摘要: 为了解决平煤十三矿保护层工作面回采遇到断层硬岩导致采煤机截割困难的问题,提出通过优化保护层深孔松动预裂爆破参数以提高工作面推进速度。利用遗传算法建立深孔松动预裂爆破参数优化模型,模型以孔深、孔径、孔间距和装药量为自变量,保护层工作面推进速度为因变量,以提高保护层工作面推进速度为优化核心,应用现场100组爆破参数,通过MATLAB计算机编程对深孔松动预裂爆破参数进行优化。试验结果显示,初始种群经过25次、50次、75次、100次迭代优化后保护层工作面的推进速度分别比原始推进速度提高7.4%、17.6%、20.2%、23.1%。100次迭代优化后,保护层工作面的推进速度逐渐稳定并趋于最优值,最终得到与最优推进速度相对应的10组优化后的爆破参数组合。结合现场施工条件,最终确定保护层深孔松动预裂爆破的孔深为40 m,孔径为75 mm,孔间距为2 m,装药量为82.5 kg。工业性试验表明,采用优化后的爆破参数,保护层断层硬岩破碎充分,采煤机截齿损耗降低31.4%,推进速度提高了22.2%,实现了提速降耗的目标。利用遗传算法优化深孔松动预裂爆破参数不仅可以提高爆破效果,减少人为干扰,而且对保护层深孔松动预裂爆破有一定的借鉴意义。

       

      Abstract: In order to solve the problem of hard rock faults encountered in the back mining of the protective layer working face of the 13 coal mine of Pingmei, it is proposed to optimise the deep hole loose presplitting blasting parameters of the protective layer to improve the advancing speed of the working face. The optimization model of deep hole loose presplitting blasting parameters is set up using genetic algorithm, the model takes hole depth, hole diameter, hole spacing and charge as independent variables, and the advancement speed of the protective layer working face as the dependent variable, and takes the improvement of the advancement speed of the protective layer working face as the core of the optimization, and applies 100 groups of blasting parameters on site to optimize the deep hole loose presplitting blasting parameters through computer programming in MATLAB. The experimental results show that after 25, 50, 75 and 100 repetitions of optimization, the propulsion speed of the protective layer working face increased by 7.4%, 17.6%, 20.2% and 23.1% compared with the original propulsion speed, respectively; after 100 repetitions of optimization, the propulsion speed of the protective layer working face gradually stabilizes and tends to be optimal, and finally 10 optimized blasting parameter combinations corresponding to the optimal propulsion speed can be obtained. Combined with the site construction conditions, the final determination of the protective layer deep hole loose presplitting blasting hole depth of 40 m, hole diameter of 75 mm, hole spacing of 2 m, and filling amount of 82.5 kg is finally obtained. Industrial tests show that using the optimised blasting parameters, the protective layer fault hard rock is sufficiently crushed, the coal mine machine blocking loss is reduced by 31.4%, and the propulsion speed is increased by 22.2%, achieving the goals of speed improvement and consumption reduction. Using genetic algorithm to optimise the parameters of deep hole loose presplitting blasting can not only improve the blasting effect and reduce human interference, but also has certain reference significance for deep hole loose presplitting blasting of protective layer.

       

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