基于正交试验的矿用车驾驶室多参数优化设计
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摘要
矿用自卸车驾驶室防翻滚(ROPS)系统优化设计的主要目的是在确保驾驶室强度、刚度和动态性能的前提下,减轻驾驶室的质量,以达到轻量化的目的;因为驾驶室本身的部件较多,每个部件对驾驶室性能影响程度也不同,因此该系统的优化设计问题属于多参数与多目标优化问题。为此采用正交实验设计对驾驶室骨架多参数进行实验设计,对设计参数进行显著度分析。运用方差分析法(ANOVA)计算各设计参数对系统响应的方差来评估各参数的显著水平.在此基础上,选取对系统响应影响较为显著的设计参数作为优化变量,利用TPS-HDMR模型构建优化变量与响应的近似模型,采用NSGA-II遗传算法进行优化求解,对优化后驾驶室进行实验验证,实验结果与仿真结果基本吻合,达到企业要求。
The main purpose of the optimization design of Dump truck cab‘s ROPS system is to reduce the weight on the premise that cab's strength, stiffness and dynamic performance are not significant changed; The cab is made up of many components and each component has different influence on the cab's performance, so the design belongs to the multi-parameter and multi-objective optimization problems. Significant degree analysis method based on Orthogonal Experimental Design was raised. This method evaluated the significant degree of each parameter through calculating the design parameter's variance to response. On the basis of these data, the design parameters which had more important influence were chosen as optimization variables, an approximate model between design variables and response was built by using TPS-HDMR, then get the optimized solutions by using NSGA-II genetic algorithm, The optimized results was verified. The experimental results agreed well with the simulation results, which can meet the requirements of the enterprise.
The main purpose of the optimization design of Dump truck cab‘s ROPS system is to reduce the weight on the premise that cab's strength, stiffness and dynamic performance are not significant changed; The cab is made up of many components and each component has different influence on the cab's performance, so the design belongs to the multi-parameter and multi-objective optimization problems. Significant degree analysis method based on Orthogonal Experimental Design was raised. This method evaluated the significant degree of each parameter through calculating the design parameter's variance to response. On the basis of these data, the design parameters which had more important influence were chosen as optimization variables, an approximate model between design variables and response was built by using TPS-HDMR, then get the optimized solutions by using NSGA-II genetic algorithm, The optimized results was verified. The experimental results agreed well with the simulation results, which can meet the requirements of the enterprise.
引文
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[3] 刘明磊. 正交试验设计中的方差分析[D]. 哈尔滨.东北林业大学, 2011:16-18.LIU MingLei. Variance analysis of orthogonal experimental design[D].Harbin: Northeast Forestry University,2011.16-18(In Chinese).
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[9] 牛艳奇, 刘 伟, 张德生. 基于NSGA-II算法的超前液压支架多目标优化设计[J]. 机械强度, 2015,37(3):450-455.NIU YanQi, LIU Wei, ZHANG DeSheng. Advance hydraulic support multi-objective optimization design based on NSGA-II algorithm [J]. Journal of Mechanical Strength, 2015,37(3):450-455(In Chinese).