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针对八连杆冲压机构的工作姿态变换,压力机构伸缩量之间的关系无法量化的问题,基于ADAMS优化八连杆冲压机构.分别分析八连杆冲压机构工作的工作原理以及工作情况,明确构件中的设计变量,并通过点位移函数表达式组建目标函数;在此基础上,以最小压力角为设计目标,构建八连杆参数优化设计数学模型,结合机械系统仿真软件AD-AMS对该数学模型进行运动仿真以及参数优化计算,得到具有较高运行效率的八连杆冲压机构仿真结果.仿真结果表明,八连杆冲压机构云顶轨迹位移方程有效性得到保证,构件部分设定的矢量模型具有有效性以及实用性. 相似文献
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李洪忠 《机械制造与自动化》2008,37(4)
通过对装载机反转六杆机构工作装置的建模分析,选取了表征该机构性能参数的设计变量,用这些参数变量作为优化设计目标函数,建立了工作装置连杆机构优化设计的数学模型. 相似文献
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在包装机上设计了一种适用于纸塑复合袋(双层袋)的八杆机构式灌装开袋装置,实现了黄皮纸外袋和塑料薄膜内袋的同步开袋和封袋,从而解决了双层袋灌装包装生产线设计中如何同步开袋顺利灌装难题。研究了八杆机构式灌装开袋装置特点,分析了八杆机构优化设计的方法,建立了以机构相位角最小值为目标函数的优化模型,运用MATLAB确定了八杆机构设计尺寸,在ADAMS中建立了虚拟机构模型并进行了运动仿真;当机构运转时,得到了末端连杆角度-时间曲线,符合黄皮纸外袋和塑料薄膜内袋同步开袋和封袋的设计要求,验证了优化设计结果的合理性,对多杆机构装置的机械设计提供了一定参考价值。 相似文献
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复合伺服驱动压边力控制执行机构建模与优化 总被引:1,自引:0,他引:1
将伺服电动机驱动与双滑块六杆机构复合,利用伺服电动机的可控性和六杆机构的速度特性,实现拉深过程的变压边力控制。在综合考虑机构输出位移中的弹性位移和刚性位移基础上,建立压边机构输入输出关系的数学模型。当机构几何参数一定时,可根据压边力与滑块位移的关系并考虑机构的变形,确定压边机构的输入速度。为优化杆系尺寸,在考虑压边工作行程和传动效果良好的基础上,以机构输出速度与压力机滑块速度相差最小(在压边力施加阶段),及机构总体尺寸最小为目标函数,优化确定了双滑块六杆机构的杆系尺寸。利用仿真软件,由前面建立的输入输出关系数学模型确定仿真输入速度,仿真结果表明,采用复合伺服驱动双滑块六杆执行机构实现压边力控制是可行的。 相似文献
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提出一种基于并联机构雅可比矩阵条件数全域参数优化方法。以并联机构6-pss为研究对象,根据机构的结构形式推导出机构的速度数学模型、建立雅可比矩阵,并用范数的形式建立雅可比矩阵条件数的数学模型;对并联机构进行参数归一化处理后,以条件数的平均值与波动值的综合值作为目标建立目标函数、给出约束条件,最后通过数值计算得到机构雅可比矩阵条件数的平均值、波动值曲线和优化目标函数值的曲线图,优化出最佳参数值,为该机构尺寸优化提供重要依据。 相似文献
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The problem of fault reasoning has aroused great concern in scientific and engineering fields.However,fault investigation and reasoning of complex system is not a simple reasoning decision-making problem.It has become a typical multi-constraint and multi-objective reticulate optimization decision-making problem under many influencing factors and constraints.So far,little research has been carried out in this field.This paper transforms the fault reasoning problem of complex system into a paths-searching problem starting from known symptoms to fault causes.Three optimization objectives are considered simultaneously: maximum probability of average fault,maximum average importance,and minimum average complexity of test.Under the constraints of both known symptoms and the causal relationship among different components,a multi-objective optimization mathematical model is set up,taking minimizing cost of fault reasoning as the target function.Since the problem is non-deterministic polynomial-hard(NP-hard),a modified multi-objective ant colony algorithm is proposed,in which a reachability matrix is set up to constrain the feasible search nodes of the ants and a new pseudo-random-proportional rule and a pheromone adjustment mechinism are constructed to balance conflicts between the optimization objectives.At last,a Pareto optimal set is acquired.Evaluation functions based on validity and tendency of reasoning paths are defined to optimize noninferior set,through which the final fault causes can be identified according to decision-making demands,thus realize fault reasoning of the multi-constraint and multi-objective complex system.Reasoning results demonstrate that the improved multi-objective ant colony optimization(IMACO) can realize reasoning and locating fault positions precisely by solving the multi-objective fault diagnosis model,which provides a new method to solve the problem of multi-constraint and multi-objective fault diagnosis and reasoning of complex system. 相似文献
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Seok-Heum Baek Seok-Swoo Cho Hyun-Su Kim Won-Sik Joo 《Journal of Mechanical Science and Technology》2006,20(3):366-375
In this paper, it is intended to introduce a method to solve multi-objective optimization problems and to evaluate its performance.
In order to verify the performance of this method it is applied for a vertical roller mill for Portland cement. A design process
is defined with the compromise decision support problem concept and a design process consists of two steps : the design of
experiments and mathematical programming. In this process, a designer decides an object that the objective function is going
to pursuit and a non-linear optimization is performed composing objective constraints with practical constraints. In this
method, response surfaces are used to model objectives (stress, deflection and weight) and the optimization is performed for
each of the objectives while handling the remaining ones as constraints. The response surfaces are constructed using orthogonal
polynomials, and orthogonal array as design of experiment, with analysis of variance for variable selection. In addition,
it establishes the relative influence of the design variables in the objectives variability. The constrained optimization
problems are solved using sequential quadratic programming. From the results, it is found that the method in this paper is
a very effective and powerful for the multi-objective optimization of various practical design problems. It provides, moreover,
a reference of design to judge the amount of excess or shortage from the final object. 相似文献
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对多个计划期内需求可预测的车间动态设备布局问题进行了研究.针对这一多目标、多约束的问题,以物流搬运和重布局费用之和、非物流关系以及面积利用率作为优化目标,将动态布局问题转化为重布局过程和多个子计划期的静态布局问题,构建了针对不等面积设备的动态多期布局问题的连续型多目标优化模型.采用带精英策略的非支配遗传算法(Non-dominated Sorting Genetic Algorithm II,NSGA-II)进行求解,克服了传统加权法求解多目标问题时加权系数难以确定和无法保证多目标同时优化的缺点,求解得到Pareto解集,供决策者根据企业实际情况优中选优.通过实例验证了本方法的有效性. 相似文献
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注射成形工艺参数是保障产品质量的关键因素。传统试错法严重依赖工艺人员的试模经验,随着注射成形工艺广泛应用于电子、航空航天等国家战略领域,产品的高端化对工艺参数智能化设置水平提出更高的要求。由于成形产品存在多方面的质量要求,且不同质量指标间可能相互制约,因此亟需一种工艺参数多目标智能优化方法,以获得不同优化目标间的帕累托最优。已有学者利用智能优化方法,如非支配排序遗传算法等,对多目标优化问题进行求解,但是此类方法需大量样本数据对质量-参数关系进行建模,存在试验次数多、且对不同材料及模具的适应性较差等问题。为解决上述问题,提出一种注射成形工艺参数多目标自学习优化方法,在优化过程中实时计算并更新各个工艺参数的梯度,并由不同质量指标的多梯度下降算法对多个目标函数进行优化,在优化过程中实现各工艺参数对产品质量影响程度的自主学习,省去了采集大量数据来建立多个质量模型的过程,实现了注射成形工艺参数的高效智能优化。在基准测试函数实验中,所提方法的优化结果与理论解的相对误差小于2%。同时数值仿真与注射成形实验结果表明,所提方法能高效获得多个优化目标的帕累托最优。 相似文献
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基于网格变形技术的白车身多目标形状优化 总被引:4,自引:0,他引:4
市场的竞争压力促使汽车厂商致力于加快车身开发的进程,而基于计算机辅助工程(Computer aided engineering,CAE)的车身结构优化技术由此而成为业内的研究热点。与传统的尺寸优化不同,形状优化在工程优化中具有更大的潜力。将网格变形技术引入形状优化,提出基于近似模型的多目标形状优化方法。利用网格变形技术定义形状变量,并根据灵敏度信息筛选优化变量;采用优化拉丁方试验设计对设计空间均匀分布样本点,进一步拟合高精度的Kriging模型;运用多目标粒子群算法,保持其余性能指标满足预期的前提下,以白车身弯曲刚度和质量为目标进行优化。研究表明,所提出的优化方法成功用于白车身的多目标优化,设计者可根据优化结果权衡各个目标,以指导最终的决策。 相似文献
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José Elias Claudio Arroyo Ana Amélia de Souza Pereira 《The International Journal of Advanced Manufacturing Technology》2011,55(5-8):741-753
This paper presents a multi-objective greedy randomized adaptive search procedure (GRASP)-based heuristic for solving the permutation flowshop scheduling problem in order to minimize two and three objectives simultaneously: (1) makespan and maximum tardiness; (2) makespan, maximum tardiness, and total flowtime. GRASP is a competitive metaheuristic for solving combinatorial optimization problems. We have customized the basic concepts of GRASP algorithm to solve a multi-objective problem and a new algorithm named multi-objective GRASP algorithm is proposed. In order to find a variety of non-dominated solutions, the heuristic blends two typical approaches used in multi-objective optimization: scalarizing functions and Pareto dominance. For instances involving two machines, the heuristic is compared with a bi-objective branch-and-bound algorithm proposed in the literature. For instances involving up to 80 jobs and 20 machines, the non-dominated solutions obtained by the heuristic are compared with solutions obtained by multi-objective genetic algorithms from the literature. Computational results indicate that GRASP is a promising approach for multi-objective optimization. 相似文献