基于分步多目标优化方法的掘进机铲板参数优化

发布时间：2018-04-12 13:25

本文选题：基值欧式距离 + 改进粒子群算法　；参考：《机械强度》2017年03期

【摘要】：针对传统及现有一些多目标优化方法在处理实际工程优化问题时需要很强的先验认识、质量差、脆弱等不足,提出了一种与基值欧式距离最小为准则的改进粒子群算法与灰色决策相结合的分步多目标优化方法;并将该方法应用于掘进机铲板参数多目标优化,对优化前后铲板推进煤岩进行了仿真分析和对比,取得了良好的优化效果,验证了该方法的可行性,为工程实际中处理多目标优化问题提供了便利与借鉴。
[Abstract]:In view of the shortcomings of traditional and existing multi-objective optimization methods in dealing with practical engineering optimization problems, such as strong prior understanding, poor quality and fragility, etc.In this paper, an improved particle swarm optimization method based on minimum Euclidean distance is proposed, which is combined with grey decision, and the method is applied to the multi-objective optimization of excavator shovel plate parameters.The simulation analysis and comparison of shovel plate propelling coal and rock before and after optimization are carried out, and good optimization results are obtained. The feasibility of this method is verified, which provides convenience and reference for dealing with multi-objective optimization problem in engineering practice.
【作者单位】：宿州学院机械与电子工程学院;辽宁工程技术大学机械工程学院;
【基金】：国家自然科学基金项目(51304107) 辽宁省教育厅创新团队项目(LT2013009) 宿州学院机械设计制造及其自动化专业带头人项目(2014XJZY31)资助~~
【分类号】：TD421.5;TP18

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