融入复杂地层动态识别的盾构施工地表沉降预测方法研究
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TU42TU94TP3-05TP312

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国家自然科学基金(51875432)、城市地下空间工程大数据智能分析与公共服务平台建设及示范应用项目(发改办高技(2017)461号)资助


An approach for predicting shield construction ground surface settlement of complex stratum using dynamical strata identification
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    摘要:

    针对盾构掘进过程中无法全面动态感知地质信息引发的难以精确预测地面沉降问题,提出了一种融入动态地层识别的地面沉降预测方法,该方法基于XGBoost动态地层识别模型,利用盾构施工参数对地层变动情况进行反向推演,明晰了地层变动时施工参数的变化规律;通过基于BPSVR的地面沉降预测融合模型最终得到距开挖面不同距离处的地面沉降量与地层情况、掘进参数的内在关联关系,从而实现了复杂地层自适应的地面沉降量准确预测。在某地铁施工区间590环数据验证下,所提的地面沉降预测方法相比传统预测方法具有更高的预测精度。

    Abstract:

    The geological information cannot be fully dynamically perceived in the shield tunneling process, which makes it difficult to accurately predict the ground settlement. To solve this problem, one kind of dynamical stratum identification model using the adaptive complex stratum changes is proposed in this paper. This method is based on the extreme gradient boosting (XGBoost) using shield construction parameters to implement the inverse deduction of stratum changes. In this way, the changing rule of construction parameters can be clarified when the stratum changes. The fusion model of error back propagation algorithm (BP) and support vector regression (SVR) for ground settlement prediction is formulated to obtain the intrinsic relationship of the ground settlement at different distances from the initial excavation face, stratum conditions and parameters of shield driving. The proposed method is validated by the 590ring data of a metro construction. Compared with the traditional method, it can achieve higher prediction accuracy.

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宫思艺,孔宪光,刘丹,仇峰涛,常建涛.融入复杂地层动态识别的盾构施工地表沉降预测方法研究[J].仪器仪表学报,2019,40(6):228-236

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  • 在线发布日期: 2022-02-10
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