基于疲劳强度的柔性曲柄滑块机构优化设计

基于伪刚体模型,以机构疲劳强度为优化目标函数,考虑各个随机变量的影响和各种约束条件的概率形式,建立了一种柔性曲柄滑块机构的优化设计模型.算例表明,该模型正确可靠,计算结果显示机构的结构尺寸和材料特性对疲劳强度影响较大.     

曲柄滑块机构中滑块匀速运动的实现

本文按给定的滑块运动规律设计了一曲柄作变长度匀速转动的曲柄滑块机构，在一般的机械中具有普遍的应用价值。     

曲柄滑块机构的最佳设计

曲柄滑块机构传动角愈大,传动性能愈好。本文以偏置曲柄滑块机构的最小传动角最大作为寻优目标函数进行机构尺寸确定。     

曲柄滑块机构在Cosmosmotion中的运动分析

曲柄滑块是机械中的一个常用机构，Cosmosmotion是Solid Works的CAE插件，可精确建立各种复杂的实际仿真模型，笔者介绍如何利用它分析曲柄滑块机构。     

曲柄滑块机构中滑块最大速度的位置探讨

根据滑块工作行程的最大速度与平均速度的比值要求设计曲柄滑块机构,首要问题是确定滑块工作行程的最大速度位置。对不同类型的曲柄滑块机构中滑块最大速度的位置问题进行探讨得出结论：偏置的曲柄滑块机构,滑块最大速度出现在曲柄与连杆相互垂直处;对心的曲柄滑块机构,滑块最大速度一般不出现在曲柄与连杆相互垂直处,随着杆长比的增大,滑块在最大速度处曲柄与连杆越接近90°。利用Excel软件对一实例求出其滑块最大速度时的位置。     

曲柄齿轮齿条组合机构的多目标优化设计

以曲柄齿轮齿条组合机构为研究对象,在考虑机构运动学及齿轮啮合特性的基础上,以齿轮摆角、齿轮角加速度以及齿轮齿条的重合度作为优化目标建立了数学分析模型;运用NSGA-Ⅱ算法对其设计参数进行了多目标优化,得到一组最优解集,从而确定了该组合机构的最优设计方案;基于Matlab仿真软件对优化前后组合机构的运动学特性进行了分析。结果表明:在保证机构运行平稳的前提下,优化后组合机构的齿轮摆角从7.365 rad增至9.875 rad,提高了该机构长行程往复运动能力。该结论为曲柄齿轮齿条组合机构的参数优化设计提供了理论参考依据。     

曲柄滑块机构用于送料装置时曲柄长度的快速确定

本文分析了曲柄滑块机构的特点，介绍了在调整送料装置用曲柄滑块机构时曲柄长度的快速确定方法。     

低速曲柄滑块六杆机构曲柄转向的规则

作者用图解法证明了曲柄转向对低速曲柄滑块六杆机构的增力效果有明显影响,并在此基础上,提出了正确设计低速曲柄滑块六杆机构曲柄转向的简要规则     

单作用往复泵偏置曲柄滑块机构

众所周知,往复泵的动力传递是通过曲柄滑块机,构实现的。长期以来,往复泵的曲柄滑块机构一直为对心式型式(以下简称对心机构)。如图1所示。然而近年来研究表明,双作甩往复泵采用对心机构是合理的,而对于单作用往复泵则应采用如图零所示的偏置曲柄滑块机构(以下简称偏置机构)更符合其工作特性,但是当偏置机构参数组合不合理时,其结果可能反而不如对心机构。所以单作用往复泵推广偏置机构     

综合考虑运动仿真结果的曲柄滑块机构的优化设计

利用MSGC软件对曲柄滑块机构进行解析设计,可以获得几个解析解。通过对这几个解析解运动仿真,分析了曲柄的位置、速度和加速度以及连杆的转角、角速度和角加速度。结果表明,增大偏距和连杆长度可以减小滑块的加速度和连杆的角加速度。根据仿真结果,从中选择最佳设计方案。MSGC软件大大降低了设计、仿真的难度,提高了设计效率及准确性。     

多目标模糊优化方法及其在可靠性设计中的应用

在基于模糊机会约束规划理论基础上,对多目标模糊优化方进行研究,通过模糊模拟求解模糊目标函数的理想极大值和极小值,建立了多目标优化问题的模糊机会约束规划模型,并给出了基于模糊模拟的遗传算法求解方法.通过对一个无约束处理的常规双目标模糊可靠性优化问题实例求解,验证了多目标模糊模拟遗传算法的有效性,并指出该算法的优点在于能较好处理多目标优化问题的分目标量纲不同及其函数值之间差距较大的情况.     

Multi-objective optimization for model predictive control

This paper presents a technique of multi-objective optimization for Model Predictive Control (MPC) where the optimization has three levels of the objective function, in order of priority: handling constraints, maximizing economics, and maintaining control. The greatest weights are assigned dynamically to control or constraint variables that are predicted to be out of their limits. The weights assigned for economics have to out-weigh those assigned for control objectives. Control variables (CV) can be controlled at fixed targets or within one- or two-sided ranges around the targets. Manipulated Variables (MV) can have assigned targets too, which may be predefined values or current actual values. This MV functionality is extremely useful when economic objectives are not defined for some or all the MVs. To achieve this complex operation, handle process outputs predicted to go out of limits, and have a guaranteed solution for any condition, the technique makes use of the priority structure, penalties on slack variables, and redefinition of the constraint and control model. An engineering implementation of this approach is shown in the MPC embedded in an industrial control system. The optimization and control of a distillation column, the standard Shell heavy oil fractionator (HOF) problem, is adequately achieved with this MPC.     

Multi-objective optimization for turning processes using neural network modeling and dynamic-neighborhood particle swarm optimization

In this paper, we introduce a procedure to formulate and solve optimization problems for multiple and conflicting objectives that may exist in turning processes. Advanced turning processes, such as hard turning, demand the use of advanced tools with specially prepared cutting edges. It is also evident from a large number of experimental works that the tool geometry and selected machining parameters have complex relations with the tool life and the roughness and integrity of the finished surfaces. The non-linear relations between the machining parameters including tool geometry and the performance measure of interest can be obtained by neural networks using experimental data. The neural network models can be used in defining objective functions. In this study, dynamic-neighborhood particle swarm optimization (DN-PSO) methodology is used to handle multi-objective optimization problems existing in turning process planning. The objective is to obtain a group of optimal process parameters for each of three different case studies presented in this paper. The case studies considered in this study are: minimizing surface roughness values and maximizing the productivity, maximizing tool life and material removal rate, and minimizing machining induced stresses on the surface and minimizing surface roughness. The optimum cutting conditions for each case study can be selected from calculated Pareto-optimal fronts by the user according to production planning requirements. The results indicate that the proposed methodology which makes use of dynamic-neighborhood particle swarm approach for solving the multi-objective optimization problems with conflicting objectives is both effective and efficient, and can be utilized in solving complex turning optimization problems and adds intelligence in production planning process.     

胶印机收纸链条机构的多目标优化设计及仿真

现代高速胶印机的收纸机构常采用链传动系统。由于链传动多边形效应,造成链条运行速度不恒定,且产生啮合冲击。现采用多目标优化设计方法,以降低链传动系统的啮合冲击、提高其传动功率、增强其可靠性为优化目标,对收纸链条进行优化,并对优化结果进行仿真。仿真结果证明了优化的合理性。     

Multi-objective path planning for unmanned surface vehicle with currents effects

This paper investigates the path planning problem for unmanned surface vehicle (USV), wherein the goal is to find the shortest, smoothest, most economical and safest path in the presence of obstacles and currents, which is subject to the collision avoidance, motion boundaries and velocity constraints. We formulate this problem as a multi-objective nonlinear optimization problem with generous constraints. Then, we propose the dynamic augmented multi-objective particle swarm optimization algorithm to achieve the solution. With our approach, USV can select the ideal path from the Pareto optimal paths set. Numerical simulations verify the effectiveness of our formulated model and proposed algorithm.     

Multi-objective reliability-based optimization for design of trapezoidal labyrinth weirs

In the present research, the reliability-based design optimization (RBDO) of labyrinth weirs has been investigated. The optimization problem is formulated such that the optimal shape of trapezoidal labyrinth weir described by a number of variables is found by minimizing the volume of the trapezoidal labyrinth weir and maximizing the reliability index. The constraint conditions are the weir geometric shape and its different ratios. In order to achieve this purpose, a framework is presented whereby non-dominated sorting genetic algorithm (NSGA-II) is integrated with monte carlo simulation (MCS) method to solve the RBDO approach of trapezoidal labyrinth weirs. The proposed method is applied to UTE Dam labyrinth weir, and the results are compared with the real one. The results show the need for design based on reliability in the labyrinth weirs that propose using RBDO for weir design. The results showed that RBDO approach can achieve a more reliable design in addition to reducing the volume of the trapezoidal labyrinth weir. Finally, the sensitivity analysis of the parameters effective on the reliability index revealed that three design variables of weir width, total upstream head and discharge coefficient are the main parameters affecting weir RBDO solution.     

基于NiTi合金丝的反射镜柔性支撑结构的应力补偿

针对大口径反射镜柔性支撑结构中柔性槽根部的应力集中问题,提出将NiTi记忆合金丝复合于柔性槽周边的结构方案,借助其预应变产生的拉应力来降低柔性槽根部的应力并保证支撑结构柔性。首先,建立了柔性槽根部的应力分布方程,得出了柔性槽危险截面位置。然后,建立了NiTi合金丝的一维本构方程,设计了桥型和U型两种复合方案,并对其进行了有限元分析。结果表明,采用U型复合的柔性支撑结构的应力改善明显优于桥型复合结构,且对结构柔性影响较小。以NiTi合金丝的拉力F为设计变量,以支撑结构的最大应力p及变形量δ为优化目标,对U型复合结构进行了参数优化设计。优化结果表明,在F为200N时有最优解,p由76 MPa降到37.9 MPa,δ由0.031mm微降到0.028mm,并且最大应力位置偏离柔性槽根部危险区域。对所提出的U型复合方案进行了随机振动试验,试验结果表明,该应力补偿设计有效降低了柔性支撑结构的最大应力。     

车辆转向机构运动精度的可靠性稳健优化设计

在车辆转向机构设计中,考虑了可控因素和噪声因素对运动精度的影响,将可靠性优化和稳健设计方法相结合,以转向机构运动精度为目标函数建立转向机构的可靠性稳健优化数学模型.把运动精度的可靠性灵敏度溶入可靠性优化设计模型之中,将可靠性稳健优化设计转化为满足可靠性要求的多目标优化问题.实例计算表明,考虑制造误差、运动副间隙等不确定因素的影响,可靠性稳健优化设计方法能有效保证转向机构的运动精度和可靠性.     

风力机齿轮箱布局的多目标可靠性优化设计

针对风力机齿轮箱布局设计中存在的问题,采用多目标可靠性优化设计方法,以风力机齿轮箱的箱体体积和齿轮体积最小化为设计目标,建立了风力机齿轮箱布局的多目标可靠性优化设计模型,分析比较了3种常见传动方案对风力机齿轮箱布局的影响,以某型号1.5 MW风力机齿轮箱为例进行了优化分析。研究结果表明,采用该设计方法得到的齿轮箱箱体体积和齿轮体积加权和值比以齿轮体积为目标的单目标设计方法更低。同时,分析结果表明,提高输入转速可大大降低齿轮箱成本。     

Multi-objective optimization of forming parameters for tube hydroforming process based on the Taguchi method

Tube hydroforming is an attractive manufacturing technology which is now widely used in many industries, especially the automobile industry. The purpose of this study is to develop a method to analyze the effects of the forming parameters on the quality of part formability and determine the optimal combination of the forming parameters for the process. The effects of the forming parameters on the tube hydroforming process are studied by finite element analysis and the Taguchi method. The Taguchi method is applied to design an orthogonal experimental array, and the virtual experiments are analyzed by the use of the finite element method (FEM). The predicted results are then analyzed by the use of the Taguchi method from which the effect of each parameter on the hydroformed tube is given. In this work, a free bulging tube hydroforming process is employed to find the optimal forming parameters combination for the highest bulge ratio and the lowest thinning ratio. A multi-objective optimization approach is proposed by simultaneously maximizing the bulge ratio and minimizing the thinning ratio. The optimization problem is solved by using a goal attainment method. An example is given to illustrate the practicality of this approach and ease of use by the designers and process engineers.