盾构机掘进过程中的决策支持系统

Decision support system in shield tunneling

盾构机掘进过程中的多系统协调控制,对于有效地控制盾构机隧道施工引起的地表变形、保证盾构安全施工和降低隧道掘进能源消耗都是极其重要的。提出了基于现场观测数据的盾构机掘进决策支持系统模型。根据盾构机掘进过程中观测的刀盘贯入度、刀盘转速、刀盘扭矩、盾构机推力和推进速度等观测数据,在地层模糊聚类分析的基础上,实现随机分布、复杂性地层特征在线辨识。以盾构机掘进参数现场观测数据为基础,利用神经网络具有的非线性映射能力、自组织和自适应能力,实现土仓压力模型的自适应建模,解决非线性、时变性、随机性和时滞性的土仓压力分布模型建模与预测控制问题。通过实时调节和控制不同位置推进油缸的推力,减少由于复杂地层的不均匀性所带来的盾构机姿态的偏差,提高隧道的成型精度。针对不同的地层,优化确定与其相适应的盾构机掘进参数,降低掘进能耗与刀具磨损,提高盾构机控制系统的顺应性。

It is very important for controling ground deformation,ensuring safely operation and decreasing energy cost to perform harmoniously control of multi-system.The decision suport system is proposed based on in-situ observed data in sheild tunneling.The soil characteristic is identified according to in-situ observed data and fuzzy clustering model of soil layer classification.By making use of nonlinear mapping and self-orgenization and self-adpting of neural network,chamber soil pressure is modeled.The forecasting control model is proposed for solving nonlinear,time-variation,time-delay and stochastic system control.Optimal tunneling parameters are determined for increasing robustness of control system and decreasing energy cost and cutter abrasion.