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隧道建设(中英文) ›› 2017, Vol. 37 ›› Issue (4): 517-521.DOI: 10.3973/j.issn.1672-741X.2017.04.019

• 施工机械 • 上一篇    

基于多目标遗传算法的复合式盾构刀盘刀具布置优化

郭京波, 王旭东, 郑丽堃, 李杰   

  1. (石家庄铁道大学机械工程学院, 河北 石家庄 050043)
  • 收稿日期:2016-06-14 修回日期:2016-08-30 出版日期:2017-04-20 发布日期:2017-04-28
  • 作者简介:郭京波(1966—),男,河北赵县人,2006年毕业于北京交通大学,车辆工程专业,博士,教授,现从事大型机械设备设计与研发工作。Email: guojingbo66@163.com。
  • 基金资助:

    国家自然科学基金资助(51275321)

Optimization of Layout of Disc Cutter of Composite Shield Based  on Multipurpose Genetic Algorithm

GUO Jingbo, WANG Xudong, ZHENG Likun, LI Jie   

  1. (School of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, Hebei, China)
  • Received:2016-06-14 Revised:2016-08-30 Online:2017-04-20 Published:2017-04-28

摘要:

为了提高复合式盾构刀盘掘进的稳定性,刀盘上滚刀的优化布置成为设计的核心问题。通过分析滚刀的受力,确定以滚刀极径与极角作为设计变量、滚刀布置原则作为约束的数学优化模型; 采用多目标Pareto解的非劣性分层遗传算法将多个目标函数同时优化,根据目标函数最优原则在Pareto最优解集中选择满足要求的优化方案。应用该优化方法对广州地铁某复合式盾构刀盘进行优化布置。研究结果显示: 优化后(边滚刀数量为9时),径向载荷合力减小了21.3%,倾覆合力矩减小了17.8%,破岩量方差减少了15%,表明所建模型及使用的多目标Pareto解的非劣性分层遗传算法是可行和有效的。

关键词: 复合式盾构, 刀盘, 刀具布置, 多目标遗传算法, 方案优化

Abstract:

The optimization of layout of disc cutter is the key to design and stability of cutterhead of composite shield tunneling. A mathematical optimization madel with polar radius and polar angle as design variables and layout principle of disc cutter as constraint is built by analyzing the force on disc cutter. And then the multipurpose functions are optimized by nondominated sorting genetic algorithm calculated by multipurpose Pareto solution, and the optimum scheme is selected. Finally, the optimum scheme is applied to the cutterhead of a composite shield used in a Metro line in Guangzhou. The results show that the radial unbalanced force is reduced by 21.3%; the upsetting moment is reduced by 17.8% and the variance of rock penetration rate is reduced by 15% after adopting the optimized scheme. It is shown that the model and the calculation method are feasible and effective.

Key words: composite shield, cutterhead, cutter layout, multipurpose genetic algorithm, scheme optimization

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