论文标题
基于多个约束和客观优化的TBM操作参数的智能决策方法
Intelligent decision-making method of TBM operating parameters based on multiple constraints and objective optimization
论文作者
论文摘要
TBM操作参数的决策对TBM安全有效的结构具有重要的指导意义，并且它一直是TBM隧道领域的研究热点之一。为此，本文将破坏岩石的规则引入了机器学习方法，并以高度准确性建立了由物理规则和数据挖掘的岩石映射双驱动。此双驱动映射随后用作目标函数和约束，以构建针对TBM操作参数的决策方法。通过搜索与约束的目标函数极端相对应的每分钟革命和渗透，可以获得最佳的操作参数。该方法在中国杭州第二水源通道的领域进行了验证，导致平均渗透率增加了11.3％，总成本下降了10.0％，这证明了开发决策模型的可实用性和有效性。
The decision-making of TBM operating parameters has an important guiding significance for TBM safe and efficient construction, and it has been one of the research hotpots in the field of TBM tunneling. For this purpose, this paper introduces rock-breaking rules into machine learning method, and a rock-machine mapping dual-driven by physical-rule and data-mining is established with high accuracy. This dual-driven mappings are subsequently used as objective function and constraints to build a decision-making method for TBM operating parameters. By searching the revolution per minute and penetration corresponding to the extremum of the objective function subject to the constraints, the optimal operating parameters can be obtained. This method is verified in the field of the Second Water Source Channel of Hangzhou, China, resulting in the average penetration rate increased by 11.3%, and the total cost decreased by 10.0%, which proves the practicability and effectiveness of the developed decision-making model.
