基于改进粒子群算法的刨煤机多目标优化设计  

Multi-objective Optimal Design for Plough Based on Improved Particle Swarm Optimization Algorithm

作　　者：毛君[1] 杨辛未 潘德文 陈洪月[1] 

机构地区：[1]辽宁工程技术大学机械工程学院,辽宁阜新123000 [2]沈阳职业技术学院,辽宁110045

出　　处：《机械设计与研究》2016年第1期168-170,共3页Machine Design And Research

基　　金：辽宁省教育厅资助创新团队项目(LT2013009);辽宁省煤矿液压技术与装备工程研究中心开放基金资助项目(CMHT-201206)

摘　　要：针对刨煤机载荷波动率、刨削比能耗及生产能力问题,根据刨煤机刨削参数和刨头结构参数,并借助改进粒子群算法对刨煤机多目标进行优化设计。优化结果表明:刨煤机载荷波动率降低了20%、刨削比能耗降低了9.8%,生产能力升高了2.5%,极大地优化了上行刨削深度、下行刨削深度、上行刨速、下行刨速、刨刀数量和刨刀间距,有效地提高了刨煤机的整机工作性能。对比不同的优化算法,采用改进粒子群算法优化的刨煤机的综合性能优于其他算法。In view of load fluctuation rate, the cutting energy consumption and production capacity of plough, according to the plough parameters of planing and plow head structure, this paper is to optimize the design of plough multi-objective based on improved particle swarm optimization algorithm. Optimization results show that plough load fluctuation rate reduces by 20%, the cutting energy consumption reduces by 9.8%, and production capacity increases by 2.5%, greatly optimizing the upgoing and downgoing cutting depth, the upgoing and downgoing cutting speed, planer number and distance, which effectively improving the whole performance of the plough. In contrast with different optimization algorithm, plough comprehensive performance, using improved particle swarm optimization algorithm, is better than others optimization algorithm.

关 键 词：刨煤机 改进粒子群算法 多目标优化设计 

分 类 号：TH122[机械工程—机械设计及理论]