基于跟管冲击钻进感知的采空区堆积形态探测与流场优化分析

    Detection of goaf accumulation morphology and optimization analysis of flow field based on follow-up casing percussion drilling perception

    • 摘要: 针对采空区存在空间封闭性强、介质分布不均、结构形态复杂等问题,基于神东上湾煤矿实践,构建了“实测-模拟-验证”协同分析框架,通过考虑“O”形圈理论模型,结合跟管冲击钻进技术和局部插值拼接融合算法,实现采空区内部裂隙形态分布的精准捕捉,精准刻画气流运动轨迹与演化规律。基于跟管冲击钻进行为感知技术,实时监测跟管冲击钻机的载荷、转速波动等特征参数,建立采空区多参数动态分布模型,反演采空区堆积形态与介质分布特征,发现工作面隅角及切眼处易出现悬顶与松散大块岩石堆积。将数值模拟与现场试验进行对比,研究结果表明:采空区孔隙率与内部风流场精度均在不同程度上有所提升,孔隙率精度提升最大为14.3%,风流速度精度提升最大为72.1%。相比传统仿真模拟技术,该方法为采空区灾害防控与资源高效利用提供可靠理论依据与技术支撑。

       

      Abstract: In view of the problems in goafs, such as strong spatial confinement, uneven medium distribution, and complex structural morphology, based on the practice at Shendong Shangwan Coal Mine, an innovative “measurement-simulation-verification” collaborative analysis framework is constructed. By considering the “O”-ring theoretical model and combining the follow-up casing percussion drilling technology with a local interpolation and stitching fusion algorithm, the precise capture of the internal fracture morphology distribution in the goaf is achieved, accurately depicting the airflow movement trajectories and evolution patterns. Based on the behavior perception technology of follow-up casing percussion drilling, characteristic parameters such as load and rotational speed fluctuations of the follow-up casing percussion drilling rig are monitored in real time. A multi-parameter dynamic distribution model for the goaf is established to invert the accumulation morphology and medium distribution characteristics of the goaf. It is found that roof suspension and loose large rock accumulations are prone to occur at the working face corner and the open-off cut. By comparing numerical simulations with field tests, the results show that the accuracy of both the porosity and the internal airflow field in the goaf is improved to varying degrees. The maximum increase in porosity accuracy is 14.3%, and the maximum increase in airflow velocity accuracy is 72.1%. Compared with traditional simulation technologies, this method provides a reliable theoretical basis and technical support for disaster prevention and control as well as efficient resource utilization in goafs.

       

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