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我国西部地区地势复杂,沟壑纵横,地下开采极易导致边坡失稳,引发采动滑坡。在地下采动沉降与滑坡体挤压上升的叠加影响下,谷底区域地表沉降值明显小于类似地质采矿条件下的平原地区。为准确预测山区谷底区域地表沉降值,基于简支梁的弹性变形理论,并借助概率密度函数建立了山区谷底区域地表沉陷预计修正模型,明确模型参数物理意义及其取值方法。依据修正模型,以实测值和预测值之差平方和最小为原则构建适应值函数,基于模拟退火粒子群算法提出新的模型参数反演方法,借助MATLAB语言编制了相应的参数反演程序。最后将研究成果应用于山西某矿,得到谷底区域预测结果中误差为73 mm,与实测值基本一致,取得了较好的工程实践效果。
The terrain in the western part of China is complex and ravines are ravaged. The underground mining can easily lead to the instability of the slope and lead to the mining landslide. Under the superimposition of underground mining settlement and landslide extrusion increase, the surface subsidence value in the valley bottom area is obviously less than that in similar geological mining conditions. In order to accurately predict the surface subsidence value in the valley bottom of mountainous area, based on the elastic deformation theory of simply supported beam, the prediction model of surface subsidence in the valley bottom of mountain area is established by means of probability density function, and the physical meaning of the model parameter and the method of its value determination are clarified. According to the revised model, the fitness function is constructed based on the square and minimum difference between the measured value and the predicted value. A new inversion method of model parameters is proposed based on simulated annealing particle swarm optimization algorithm. Finally, the research results are applied to a mine in Shanxi Province. The error of prediction results obtained in the valley bottom area is 73 mm, which is basically consistent with the measured values and achieved good engineering practice results.