The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can caus...The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.展开更多
针对多目标工艺规划与车间调度集成问题(multi-objective integrated process planning and scheduling,MOIPPS),以最小化完工时间和生产能耗最低为优化目标,提出了一种考虑全局和局部最优的改进混合优化算法。通过分析集成系统工艺设...针对多目标工艺规划与车间调度集成问题(multi-objective integrated process planning and scheduling,MOIPPS),以最小化完工时间和生产能耗最低为优化目标,提出了一种考虑全局和局部最优的改进混合优化算法。通过分析集成系统工艺设计和生产调度两个问题的区别与联系,搭建了多目标问题模型和解决框架。针对两阶段集成问题提出混合优化算法,对工艺阶段采用全局搜索算法,为集成系统提供多种工艺加工方案,保证集成算法的全局搜索性能;针对调度阶段设计一种改进禁忌搜索算法,通过交叉与随机抽样扩大解的分布范围,使用邻域禁忌搜索使得算法快速收敛,并采用Pareto非支配排序获得全局最优解。实验对比分析,验证了所提算法在求解多目标工艺规划与车间调度集成问题的高效性和稳定性。展开更多
针对干旱区水资源分配不合理的问题,以新疆开都河流域水资源为研究对象,以流域水-能源-生态综合收益最高为目标,建立水资源多目标优化配置模型,采用基于参考点的非支配排序进化算法(reference-point based many-objective,NSGA-Ⅲ)对模...针对干旱区水资源分配不合理的问题,以新疆开都河流域水资源为研究对象,以流域水-能源-生态综合收益最高为目标,建立水资源多目标优化配置模型,采用基于参考点的非支配排序进化算法(reference-point based many-objective,NSGA-Ⅲ)对模型进行求解。针对优化方案选择问题,以经济效益、社会效益和生态效益为准则层构建流域水资源最适配置方案评价指标体系,采用层次分析法对优化结果进行评价分析。结果表明:最适配置方案相较于传统配置方案,水库发电量增加5.83%,农业经济效益减少2.34%,生态效益提高40.08%;当地种植结构需进行适当调整,应增加玉米和西红柿的种植面积,减少小麦、棉花和辣椒的种植面积;博斯腾湖大湖和小湖水位均达到最适生态水位。研究成果可为当地制定水资源配置方案提供决策参考,有重要的理论意义和应用价值。展开更多
基金Projects(U22B2084,52275483,52075142)supported by the National Natural Science Foundation of ChinaProject(2023ZY01050)supported by the Ministry of Industry and Information Technology High Quality Development,China。
文摘The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.
文摘针对多目标工艺规划与车间调度集成问题(multi-objective integrated process planning and scheduling,MOIPPS),以最小化完工时间和生产能耗最低为优化目标,提出了一种考虑全局和局部最优的改进混合优化算法。通过分析集成系统工艺设计和生产调度两个问题的区别与联系,搭建了多目标问题模型和解决框架。针对两阶段集成问题提出混合优化算法,对工艺阶段采用全局搜索算法,为集成系统提供多种工艺加工方案,保证集成算法的全局搜索性能;针对调度阶段设计一种改进禁忌搜索算法,通过交叉与随机抽样扩大解的分布范围,使用邻域禁忌搜索使得算法快速收敛,并采用Pareto非支配排序获得全局最优解。实验对比分析,验证了所提算法在求解多目标工艺规划与车间调度集成问题的高效性和稳定性。
文摘针对干旱区水资源分配不合理的问题,以新疆开都河流域水资源为研究对象,以流域水-能源-生态综合收益最高为目标,建立水资源多目标优化配置模型,采用基于参考点的非支配排序进化算法(reference-point based many-objective,NSGA-Ⅲ)对模型进行求解。针对优化方案选择问题,以经济效益、社会效益和生态效益为准则层构建流域水资源最适配置方案评价指标体系,采用层次分析法对优化结果进行评价分析。结果表明:最适配置方案相较于传统配置方案,水库发电量增加5.83%,农业经济效益减少2.34%,生态效益提高40.08%;当地种植结构需进行适当调整,应增加玉米和西红柿的种植面积,减少小麦、棉花和辣椒的种植面积;博斯腾湖大湖和小湖水位均达到最适生态水位。研究成果可为当地制定水资源配置方案提供决策参考,有重要的理论意义和应用价值。
