中国机械工程

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基于Pareto最优原理的钻机钻进参数多目标优化

王凯;王荣鹏;刘宇;宋桂秋   

  1. 东北大学机械工程与自动化学院,沈阳,110819
  • 出版日期:2017-07-10 发布日期:2017-07-10
  • 基金资助:
    辽宁省科技创新重大项目(2015106003);
    辽宁省重大装备制造协同创新中心项目

Multi-objective Optimization of Drilling Parameters Based on Pareto Optimality

WANG Kai;WANG Rongpeng;LIU Yu;SONG Guiqiu   

  1. School of Mechanical Engineering and Automation, Northeastern University, Shenyang,110819
  • Online:2017-07-10 Published:2017-07-10

摘要: 针对某双管定向钻机,提出了基于Pareto最优原理的钻进参数多目标优化方法。该方法根据钻机性能与工况,考虑水力对钻头比能影响,确定了钻进参数优化模型。针对罚函数处理约束条件的不足,引入了改进约束条件处理策略,提出了基于小生境思想拥挤度值计算方法及自适应交叉和变异算子。测试了改进算法的性能,并将改进算法用于求解基于某煤矿工程实际建立的钻机钻进参数优化模型。研究结果表明:与NSGA-Ⅱ和MOPSO算法相比,改进算法在求解测试问题时具有更好的收敛性与分布性。利用改进算法求解实际问题时得到的Pareto前端解集分布均匀,而且有效提高了机械钻速,延长了钻头寿命并降低了钻头比能。

关键词: 钻机, 钻进参数, 带约束多目标优化, 约束主导原理, Pareto最优解

Abstract: A multi-objective optimization of drilling parameters method based on Pereto principle was put forward to optimize horizontal directional drill machine. The optimization model of drill parameters was developed. Modifications were made based on NSGA-Ⅱ due to the deficiency of penalty function method in handling constraints. Therefore, an effective constraints handling strategy utilizing constrained domination principle was introduced. To prevent premature, and accelerate the convergence speed towards optimal Pareto front, the original crowding distance calculation method was modified based on the niche concept. A new adaptive crossover and mutation strategy was put forward. Finally, the modified algorithm was applied to optimization model of drilling parameters which was built based on a coal mine. The results show that the modified algorithm has better convergence and distribution compared with NSGA-Ⅱ and MOPSO when solving test problems. The distribution of solution set is evenly when applying the algorithm to solve optimization model of drilling parameters. It improves the mechanical drilling speed effectively, extentes the life of drilling and decreases the energy ratio of drilling.

Key words: drilling machine, drilling parameter, constrained-multi-objective optimization with evolutionary algorithm; constrained-dominated principle; , Pareto optimal solution

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