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基于PMOPSO方法的H型铲齿凸轮优化设计
引用本文:梁松,张义民,胡鹏.基于PMOPSO方法的H型铲齿凸轮优化设计[J].工程设计学报,2017,24(2).
作者姓名:梁松  张义民  胡鹏
作者单位:东北大学 机械工程与自动化学院机械可靠性与动力学技术中心,辽宁 沈阳,110819
基金项目:国家自然科学基金资助项目,国家重点基础研究发展计划(973计划资助项目),"高档数控机床与基础制造装备"科技重大专项课题
摘    要:给出一种H型铲齿凸轮的标准设计方法,用于解决多升程H型铲齿凸轮的优化设计问题。针对传统铲齿凸轮存在的过渡点冲击问题,提出基于H型凸轮从动件运动规律的铲齿凸轮设计方案。以凸轮面积为设计目标函数,以从动件的偏置量和初始位移为设计变量,在凸轮一般设计准则的基础上,考虑理论廓线曲率范围和压力角分布的约束条件,建立H型铲齿凸轮的优化设计模型。多升程H型铲齿凸轮的优化设计问题具有约束条件多、非线性强和计算复杂度高的特点,将多项式变异算子和标准粒子群优化结合,提出多项式变异粒子群优化方法。以此优化方法为基础,通过构造罚函数处理设计约束,分别求解三升程和四升程的H型铲齿凸轮优化设计问题。计算结果表明,提出的标准设计方法可显著降低多升程H型铲齿凸轮的工作轮廓面积,使铲削机构更加紧凑。

关 键 词:铲齿凸轮  多项式变异算子  粒子群优化

Optimization design of H-type relieving cam based on PMOPSO method
LIANG Song,ZHANG Yi-min,HU Peng.Optimization design of H-type relieving cam based on PMOPSO method[J].Journal of Engineering Design,2017,24(2).
Authors:LIANG Song  ZHANG Yi-min  HU Peng
Abstract:A standard design approach which is used for the multi-rise H-type cam optimization design is proposed.Aiming at the severe shocking problems of traditional relieving cams during the transient process,the relieving cam design scheme based on motion law of H-type cam followers was proposed.Taking the cam area as the object function and the follower offset and initial displacement as the design variables, H-type relieving cam optimization design model which considered the constrains included the range of theoretical cam surface curvature and the distribution of pressure was proposed based on general design criterions.The optimization problem was featured by multi-constraints, high nonlinear and intensive computation.PMOPSO (polynomial mutation operator particle swarm optimization) method combined polynomial mutation operator and standard PSO method was proposed.By means of PMOPSO method and constraint-handlings of penalty function, the 3-rise and 4-rise H-type relieving cam optimization problems were solved separately.The results showed that the approach was able to decrease the working profile area of multi-rise H-type cam significantly.Meanwhile, the shovel mechanism was more compact.
Keywords:relieving cam  polynomial mutation operator  particle swarm optimization
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