基于能量守恒的机械零件可靠性模糊多目标优化方法研究

多目标优化中各子目标函数权值分配应采用动态变化的赋值方法，并且应将基于有效解的常规多目标优化模型拓展为基于软计算满意解的模糊多目标优化模型。从能量守恒与转化以及系统论方法的角度，对多目标优化进行了阐述。利用模糊集理论中隶属函数的特性，将各子目标函数模糊化处理为满意度函数，建立了广义均匀定常满意度函数场下的模糊多目标优化的能量关系模型，提出了由协调校正权函数、广义有势力函数构成的多目标满意解总评价函数的方法。给出机械零件可靠性多目标满意解优化实例，进行可行性验证。     

Multi-objective optimization of cycloidal gear based on segmental modification of pressure angle

In order to get the optimal profile of cycloid gear after sectional modification, a multi-objective optimization design method is proposed that considers both the modification parameters and macro-parameters of the cycloid gear. An algorithm of meshing force, meshing efficiency and anti-gluing ability between the cycloid gear and the pin gear was derived, and the related independent parameters were extracted as optimization variables. Taking high efficiency, high strength and light weight as the objective, the mathematical models of double-objective and three-objective optimization were established, and the influence of key design variable on the objective function was analyzed, and NSGA-II multi-objective genetic algorithm was used to solve the Pareto optimal solution of the optimization mathematical model. Results show that the optimized parameters can significantly improve the meshing efficiency, reduce the volume and meet the design requirements of high strength, high efficiency and lightweight on the premise of ensuring the strength of cycloid gear surface.

     

动态多目标优化的运动物体图像分割

对小区背景下运动物体图像进行分割时多使用单目标或多目标优化方法,这类方法不能有效适应目标的动态变化,因此本文提出一种动态多目标图像分割优化方法。该方法将时间及环境动态因素作为动态因子,利用K均值(KMeans)算法和和模糊C均值(FCM)聚类算法构造多目标函数;结合动态多目标粒子群算法(DMPSO),使用背景差分法定义环境变化规则,实现动态多目标的图像分割。根据DMPSO算法优化后的聚类结果,分别与K-Means和FCM聚类方法得到的结果进行了对比。结果表明,动态多目标优化的Pareto最优解集分布均匀,图像分割准确率可达到95%,对图像识别的准确率可达到90%,具有较高的识别能力,能满足确定背景下运动物体的准确识别。     

Effect of driving functions with different jerk and accelerating time length on dynamic performance for mechanical systems: analysis and optimization

We studied the methods that are used for analyzing and optimizing the dynamic performance of mechanical systems in the startup stage under different driving functions. Especially, we considered the effects of joint clearance and component flexibility. The dynamic model of mechanical system is the basis of our methods. A higher order polynomial was used for describing the driving form of mechanical system, and the initial jerk and accelerating time length were employed to determine the specific driving function. Besides, we presented three performance evaluation parameters for mechanical system and introduced surrogate models to improve performance evaluation efficiency. Then, the optimal driving function was determined by using the surrogate models and a multi-objective optimization algorithm. Finally, a planar slider-crank mechanism with a clearance joint was taken as an example to demonstrate our methods.

     

多目标混合流水车间作业调度的演化算法

针对多目标条件下混合流水车间作业调度的优化问题，提出了一种在优化进程中能够动态调整适应度分配的演化算法。该算法采用矩阵编码描述多阶段并行机调度方案，结合问题的优化模型，对每一代Pareto解在各目标方向上的改善程度进行度量，进而通过多目标的选择性权重系数计算种群个体的适应度，以获得在改善指示方向上的选择压力。通过BENCHMARK问题测试和实际算例分析，表明新算法的性能优于现有的求解算法，特别是对于高维多目标优化问题，能够获得较高的演化收敛速度。     

基于状态空间的车辆耦合振动系统分析及优化

以车辆子系统间耦合关系为出发点,基于状态空间理论提出了以子系统耦合系数和相对衰减系数为考察指标的车辆子系统振动传递特性研究方法。采用拉丁超立方设计分析了悬置参数对系统耦合程度的影响,研究了耦合和子系统振动衰减的关系;采用非支配序列遗传算法进行了多目标优化并获取了最优解集,并结合子系统传递函数来验证结果。研究结果表明,以相对衰减系数最小化为目标,综合考虑发动机-底盘和车身-底盘子系统的耦合关系可有效改善车辆平顺性。     

Lightweight design of hinge beam based on Kriging agent model

This paper presents an optimization method based on the Kriging and multi-objective genetic algorithm. First, taking the hinged beam structure of the cubic diamond press as the design object, the optimization design mathematical model was established with the mass as the objective function, the stress and displacement peak as the constraint conditions. Second, in combination with SolidWorks and ANSYS Workbench, parametric modeling analysis was conducted to obtain a large number of sample points sparing less time, and the agent model constructed by Kriging was trained and verified. Finally, taking advantage of global search of the multi-objective genetic algorithm, a lightweight design was realized and the mass of the hinge beam structure was effectively reduced, which would be a guiding significance for the lightweight design of other mechanical parts.

     

基于MapReduce和多目标蚁群算法的制造云服务动态选择算法

基于云计算技术和云服务技术研究了云服务的动态选择问题,给出了云制造服务层次化模型,提出了一种基于MapReduce和多目标蚁群算法的制造云服务动态选择算法(CSSMA)。依据CSSMA设计了多目标蚁群算法、Map函数、Reduce函数和优化策略等,并将其分布式并行运行于制造云平台中。仿真实验结果表明:CSSMA具备良好的处理大规模问题的能力,适用于制造云服务动态选择问题的求解。     

Trajectory optimization of an electro-hydraulic robot

The electro-hydraulic robot has great driving torque and plays an irreplaceable role in manufacturing. In this paper, a trajectory planning method for a 6-DOF electro-hydraulic robot based on time-energy-jerk is proposed and realized. A multi-objective function of the electro-hydraulic robot about working efficiency, impact, stability and energy consumption factors was built, at the same time, the kinematic and dynamic constraint functions were also built. The multi-objective trajectory function of the robot was optimized by using the non-dominated neighborhood immune genetic algorithm, and the optimal position, velocity, acceleration and jerk planning curves of each joint were obtained. In the experiment, the flow output curves of the hydraulic system of joint 6 based on fuzzy-PID control strategy under no-load, 1.5 kg load, 4 kg load were obtained, and show that the velocity and position trajectory of the joint can be well controlled using the presented fuzzy PID control strategy.

     

基于仿真的数控铣削加工参数优化研究

针对数控铣削加工参数优化问题,通过加工仿真,计算每一走刀步的切削深度和切削宽度并划分区间。在每一个由组合划分区间内所有刀步构成的一个加工特征组合段上建立了多目标优化模型,模型采用遗传算法对每一加工特征组合段的加工参数进行优化,自动修改NC程序中的加工参数并反映优化结果。应用实例证明,提出的多目标优化模型和优化求解算法正确、有效。     

A new method based on LPP and NSGA-II for multiobjective robust collaborative optimization

The multiobjective robust collaborative optimization framework consists of optimization both at the system and autonomous subsystem levels. Linear physical programming is used in the system level optimization, which avoids the difficulty in choosing the multidimensional Pareto set. The non-dominated sorting genetic algorithm (NSGA-II) is used in the subsystem optimization with physical objectives. The interdisciplinary incompatibility function and physical objectives have different priority levels. At the first priority level, the best individual should be in the feasible region of the subsystem. At the second priority level, the interdisciplinary incompatibility function of the best individual should be no more than the feasibility threshold. The physical objectives are improved after the achievement of the above levels. A method for producing initial population with feasibility and diversity is proposed to improve the calculation efficiency and accuracy of the subsystem optimization at the first priority level. A method for setting dynamic feasibility threshold is proposed for the non-dominated sorting to help the physical objectives to obtain better solutions at the second priority level. Finally, the results of the speed reducer show that the presented method is efficient.     

基于ANSYS的桥式起重机多目标动态优化设计

针对目前桥式起重机设计大多以静强度作为主要设计准则,设计模型修改困难等问题,以浙江金港船业的10t-34．5m桥式起重机整体结构为设计原型,采用有限元法动态分析理论,建立系列通用的桥式起重机有限元参数化模型,并对其进行动态分析,分析结果作为优化设计模型的目标函数。采用改进的非支配排序遗传算法（NSGA—Ⅱ）,对结构进行多目标动态优化设计,有效减轻了桥式起重机的质量,提高了桥式起重机金属结构的动态性能,为桥式起重机的设计提供了一定的理论依据。     

一种改进遗传算法在离合器参数优化中的应用

针对离合器摩擦片参数优化过程中多目标、多参数、多约束的特点,提出了一种改进遗传算法。采用层次分析法对分目标函数的权重系数进行了初始分配,引入参数间组合度系数和参数的敏感度系数,将组合度系数用于交叉变异中,将敏感度系数用于权重系数动态调整中。以东方红-LA3004拖拉机换挡离合器为优化算例,分别基于传统遗传算法和改进遗传算法对离合器参数进行了优化,将两种优化结果进行了对比分析,结果表明,改进遗传算法能在得到全局最优解的同时,提高优化效率。     

某机载天线射频线缆布线设计与长度优化

针对某机载天线射频线缆布线设计与长度优化问题,提出人工布线与多目标优化相结合的方法。以线缆总重量最小为目标,线缆分组等长为约束条件,构建线缆长度多目标优化数学模型,采用MATLAB的遗传算法函数完成问题求解,有效简化设计过程,提高布线效率。     

液压混合动力矿用卡车系统参数多目标优化研究

以液压混合动力矿用卡车为研究对象,综合考虑能量管理控制参数与传动系参数对燃油经济性和小型化目标的影响。选取能量管理控制参数与传动系参数为优化变量,以矿用卡车的动力性能为约束条件,建立燃油经济性和小型化为目标的多目标优化评价方法。选取NSGA-II算法对混合动力系统进行多目标的优化。结果表明：在满足动力性约束的基础上,优化后等效百公里油耗下降了14.86%,爬坡度上升了12.39%。该多目标优化方法的收敛性和分布性较好,得到的pareto解集能够给液压混合动力矿用卡车的设计提供更多的方案进行选择,体现了基于NSGA-II算法的多目标优化的优势。     

基于Pareto集和Bingham模型的磁流变减振器多目标优化与试验验证

磁流变减振器和半主动悬架可以同时兼顾车辆操纵稳定性和行驶安全性,是目前汽车电子技术的研究热点。磁流变减振器的设计大多只考虑某一优化目标,基于Pareto集多目标方法和带精英策略的非支配排序遗传算法(the elitist Nondominated Sorting Genetic Algorithm,NSGA-Ⅱ),以阻尼力和动力可调系数为优化目标,设定7个优化变量,构建了车用磁流变减振器多目标优化模型与实现算法。分析了7个优化变量对阻尼力和动力可调系数的设计敏感性,并通过有限元分析和试验验证优化解的可靠性。研究发现:阻尼通道间隙对优化目标影响最大,最大阻尼力和最大动力可调系数呈负相关关系。该多目标优化计算的最优解满足实际工程需求,证明了提出的优化方法快速有效,为磁流变减振器的设计提供了可靠的工具。     

QUADRATIC OPTIMIZATION METHOD AND ITS APPLICATION ON OPTIMIZING MECHANISM PARAMETER

In order that the mechanism designed meets the requirements of kinematics with optimal dynamics behaviors, a quadratic optimization method is proposed based on the different characteristics of kinematic and dynamic optimization. This method includes two steps of optimization, that is, kinematic and dynamic optimization. Meanwhile, it uses the results of the kinematic optimization as the constraint equations of dynamic optimization. This method is used in the parameters optimization of transplanting mechanism with elliptic planetary gears of high-speed rice seedling transplanter with remarkable significance. The parameters spectrum, which meets to the kinematic requirements, is obtained through visualized human-computer interactions in the kinematics optimization, and the optimal parameters are obtained based on improved genetic algorithm in dynamic optimization. In the dynamic optimization, the objective function is chosen as the optimal dynamic behavior and the constraint equations are from the results of the kinematic optimization. This method is suitable for multi-objective optimization when both the kinematic and dynamic performances act as objective functions.     

Multi-objective optimization of electric-discharge machining process using controlled elitist NSGA-II

Parametric optimization of electric discharge machining (EDM) process is a multi-objective optimization task. In general, no single combination of input parameters can provide the best cutting speed and the best surface finish simultaneously. Genetic algorithm has been proven as one of the most popular multi-objective optimization techniques for the parametric optimization of EDM process. In this work, controlled elitist non-dominated sorting genetic algorithm has been used to optimize the process. Experiments have been carried out on die-sinking EDM by taking Inconel 718 as work piece and copper as tool electrode. Artificial neural network (ANN) with back propagation algorithm has been used to model EDM process. ANN has been trained with the experimental data set. Controlled elitist non-dominated sorting genetic algorithm has been employed in the trained network and a set of pareto-optimal solutions is obtained.

     

某火炮协调器多学科一体化设计优化

为了解决传统火炮优化设计中单学科建模分析的不足,采用多学科一体化设计优化方法对某火炮协调器系统进行了研究。通过对电气控制、液压、机械三个学科及学科间耦合关系的分析,建立了协调器结构控制一体化分析模型,结合多目标进化算法,对建立的一体化分析模型进行了设计优化研究。与原设计相比,优化后的设计使系统拥有更优的综合性能。     

基于模糊优化下离散误差非线性参数识别方法研究

根据结构系统动态特性分析的模糊性,试验测试数据和离散误差选择的模糊性,提出了一种基于模糊优化下解决离散误差信号非线性参数识别的思想和方法。根据模糊数学权函数理论,建立模糊优化函数,推导出一种适用于动态结构系统响应信号高精度参数识别方法——离散误差信号模糊优化非线性参数识别算法。作为实例,对MG1432B整机的动态特性进行模糊分析,并将其响应信号测试数据进行模糊优化非线性参数识别,从而精确地识别出九阶模态参数,并绘出相应点的幅、相频拟合曲线。验证结果说明,此方法具有较高的识别精度和工程应用价值。