Hu Min, Zhang Haolan, Wu Bingjian, Li Gang, Zhou Li
SILC BusinessSchool, Shanghai University, Shanghai, 201800, China.
SHU-SUCG Research Centre for Building Industrialization, Shanghai University, Shanghai, 200072, China.
Sci Rep. 2022 Oct 29;12(1):18226. doi: 10.1038/s41598-022-22948-w.
The sudden decline in the attitude control performance is a common abnormal situation during shield tunneling. When the problem happens, the shield driver will have difficulty controlling the shield's attitude, which will cause the shield to deviate from its design axis and affect the quality of the tunnel. The causes behind poor control performance are usually complicated, so how to choose appropriate countermeasures is a challenging problem. Based on the above issues, this paper proposes the Interpretable Predictive Model for Shield attitude Control Performance (IPM_SCP). The model first predicts the current shield control performance through the extreme gradient boosting (XGBoost) sub-model and then uses the Shapley additive explanation sub-model to interpret the model output. The model was tested on the left-line tunnel of the Hangzhou-Shaoxing railway project in the Ke-Feng section. The results reveal that the model could effectively predict the control performance of the shield and give the most influential parameter and the direction in adjusting the parameter to improve the shield's attitude control performance when the control performance decreases. Therefore, IPM_SCP gives the correct parameter adjustment instructions when the shield's attitude control performance declines, and eventually improves tunnel construction quality and efficiency.
盾构隧道施工过程中，姿态控制性能突然下降是一种常见的异常情况。问题发生时，盾构司机难以控制盾构姿态，导致盾构偏离设计轴线，影响隧道质量。控制性能不佳背后的原因通常很复杂，因此如何选择合适的应对措施是一个具有挑战性的问题。基于上述问题，本文提出了盾构姿态控制性能可解释预测模型（IPM_SCP）。该模型首先通过极端梯度提升（XGBoost）子模型预测当前盾构控制性能，然后使用Shapley加法解释子模型解释模型输出。该模型在杭绍铁路柯丰段左线隧道进行了测试。结果表明，该模型能够有效预测盾构的控制性能，并在控制性能下降时给出最具影响力的参数以及调整参数以改善盾构姿态控制性能的方向。因此，IPM_SCP在盾构姿态控制性能下降时给出了正确的参数调整指令，最终提高了隧道施工质量和效率。
