一个针对复杂机械结构的多目标优化集成方法毕业课程设计、中英文翻译

目录1、英文文献翻译11.1 An integrated method of multi-objective optimization for complex mechanical structure11.2中文翻译112、专业阅读书目182.1 机械设计182.2机械设计182.3现代工程图学192.4机电传动控制192.5材料力学202.6互换性与技术测量202.7理论力学212.8机械设计课程设计212.9机械制造技术212.10机械制造基础22181、 英文文献翻译1.1 An integrated method of multi-objective optimization for complex mechanical structure Now someone has put forward an integrated approach for complex mechanical structures of multi-objective optimization, and integrated prototyping, finite element analysis and optimization. In order to explore it for the advantages of the traditional method, the robot in the mixed-mode aerial vehicles (HMAWV) have adopted this optimization, the purpose of doing so is to increase their area of work, lower costs in sufficient strength to the premise will be designed variable geometry, and geometric dimensions to the design parameters, NLPQL NSGA - II of the comprehensive application to obtain the best solution. The results showed that this integrated approach is more efficient than the exhaustive search algorithm. NSGA - II can be close to the global cutting-edge technology, and NLPQL and NSGA - II The relative error is negligible. Therefore, this integrated approach is effective, and shows its potential in the field of engineering applications.1、Introduction In order to increase market competitiveness, structural design, analysis and optimization of the same like concurrent engineering have been integrated into the concept development stage. Scientific literature to design a new product in a variety of technologies, including computer programming more and more popular, because, along with the advance of computer and software technology revolution, and the superiority of the programming reflects the efficiency and accuracy.Traditional computer programming is like this: First, engineers draw a sketch of the product; the use of computer-aided design (CAD) software to the geometric model Subsequently, most of the engineers to the CAD model is imported into finite element analysis tools to evaluate it Finally, structural performance, some commercial software from ANSYS, MSC / NASTRAN, ABAQUS, to complete the size and topology optimization. Have been many important advances in this direction, some researchers use the domestic research tools MSC / NASTRAN to achieve structural optimization al. Barkeret secondary development of the MSC / NASTRAN, and has been confirmed by two instances. Recently, Hansen, and Horst, according to the refined finite element model developed a multi-level optimization procedure, that is the first step with the development to find slightly optimize the topological parameters, the second step application of MSC / NASTRAN optimization of the thickness and longitudinal section of the model, but simplify the boundary conditions. Although many efforts in this way, but due to the traditional optimization algorithm of the detention, the solution is still trapped in a region, and ignore the many nonlinear factors that such a program is not accurate.This novel method is a synchronous finite element software integrated into the optimization procedure. It uses a random search algorithm as the optimization method, which not only can prevent the optimizer is trapped in the local area, and can achieve accurate global optimal solution. The Many optimize the tool has been carried out development in the the field of literature, CAOSS appear than an earlier, it is a module expansion finite element program. Bakhtiary et al. Proposed a new interface between CAOSS and MSC / NASTRAN, then Meskeet al this interface the leading FEMsolvers, MSC / NASTRAN, MSC / Fatigue, ABAQUS, MSC. Marc and MSC.Patran the way. Proprietary software DynOPS is a choice as other optimization tools, The Giger, and Ermanni use DynOPS finite element analysis software ANSYS is applied to the development of composite fiber reinforced plastic motorcycle rims. Hilmann introduced an optimization software, the SFE concept, this software is used in the automotive industry in Germany. ISIGHT is another optimization software, which includes a wide range of classical and non classical optimization methods, such as Design of Experiments (DOE), the approximate exchange technology, multi-criteria analysis methods and quality engineering. Qian and Yuan successfully UG, of ICEM-of CFD and FLUENT integration to ISIGHT, and the Design of Experiments (DOE) is used to design the underhood. Later, Cullimore et al. In order to optimize an observation space telescope, the MSC / NASTRAN and Fluent integrated into ISIGHT. Although many optimization tool has been extensively developed, but the multi-objective optimization of complex mechanical structures is still a challenge.In this study, a complete design methodology and the structure of multi-objective optimization is advanced. Finite element analysis using ANSYS software and optimization algorithms to be integrated into a commercial optimization the software ISIGHT-FD, and confirmed these integration process. As an application example, the multi-objective optimization of robot development, the purpose of doing so is to expand the scope of its application, under the premise of sufficient strength to reduce its quality by optimizing the geometric dimensions. Whether it is based on the rate of change of the classical algorithm or evolutionary algorithm are adopted to obtain the best solution.In the second part discusses the integration process with finite element model, simulation, and optimization algorithms. In the third section, the robot on the mixed-mode high-altitude operations car (HMAWV,) A case study was put out. Application contact element analog connections, to verify the results of the finite element analysis, the development of experimental stress analysis. And adoption of NLPQL and NSGA-II to the excellent of manipulation cases. Compare the results of the optimization algorithm. Furthermore, in order to verify that the best solution, the NSGA-II parameters define a different value. In the fourth section, conclusions and future scholars to study and discuss.2、Parallel methods of integration proceduresStructural optimization of the key is to have the ability to automatically generate a variety of design of the virtual prototype model. Concurrent design and optimization, for the realization of the four basic steps to verify that the parametric model. ANSYS provides a parameterized language-modeling approach of ANSYS Design Language (APDL), can be used to automate the same task or even to establish the parameters of the mathematical modeling. Therefore, the automatic grid files and computing may be defined APDL file and the depth of carburized layer on inverse problem can also receive the analysis results. In addition, the use of finite element analysis software ANSYS, the processing mode to run the graphical user interface (GUI) will not appear and the preparation of the corresponding computer program, just run in the background command. APDL file including the design variables, and the output file, including the constraints and objectives, to optimize the control file can only integrate the two documents, the parallel optimization based on finite element analysis.Figure 1 illustrates a synchronous design and optimization process, as shown in the process is a cyclical process. ISIGHTFD control unit, which controls the performance of finite element analysis and optimization. In this simulation, finite element analysis and optimization to manual execution. Therefore, this process can improve the optimization efficiency, expand the design space of the variables. Fig.1. Process flow of integrated optimization2.2 Simulation process The text of the compiler can generate the APDL documents, and APDL file can define any completed command in a graphical user interface (GUI) mode or batch mode. There is a level of classification, geometric quantities is the top level, then the surface, then line keypoint minimum. Therefore, the two modeling methods can be applied to the APDL file, whether it is from top to bottom or from bottom to top. In the present study, the method adopted from the bottom to the top of the basis for the definition, because of coordination, and their location can be parameterized. When we defined a geometric element that may arise special element type. H-refinement and p-refinement is refined by two grid structure analysis. H-refinement mesh improve the accuracy of an increasing number of elements, and p-refinement meshing accuracy improve to increase the degree of the elements of the shape function, but the p-refinement cost of more computation time. regular application of h-refinement has a higher solution precision. Verify the quality of elements, many of the provisions need to check they are the aspect ratio deviates from 90 , in parallel to the edge of degree of deviation, maximum degree angle and customized values can be defined users. If there is no warning and error, it shows that all these terms are satisfied, and calculations can begin. When the solution has been completed, the results can be from the depth of carburized layer inverse problem solving, reading and written into an output file, the file will provide constraints and objective function optimization.2.3 Optimization algorithmFor multi-objective optimization, the best way does not exist here, some only a number of ways. Only consider one factor in this program must be superior than other options, but taking into account other factors, this program than other programs, some of the These programs are famous as the best Pareto program.In the literature, many algorithms have been developed for the best Pareto program.In general, they can be divided into two, a listing search, including the greedy algorithm, hill-climbing algorithm, branch and bound algorithm, depth-first search algorithm to search for answers in some areas of the given design, they can solve problems in practical applications. But it can not be used in multiple-scale or complex non-linear problems, to spend a huge computational cost. The other is a random search algorithms, including random walk, tabu search, simulated annealing algorithm, Monte Carlo algorithm, evolutionary algorithm, the algorithm is supposed to solve the problem, irregular need to define the evaluation function for direct search to solve the problem. Compared to enumerate the search, random search better solutions to complex problems.The genetic algorithm (GA) is one of the most prominent random search methods, and it has been widely used. It comes from the principles of natural genetics and natural selection. The basic principle of genetics is to borrow to build artificial demand for the minimum amount of information on health algorithm. Deb introduced the basic theory and operating principle of the genetic algorithm (GA).In recent years, in order to find the best Pareto program, developed a new version of the various genetic algorithm, Knowles and Corne of PAES, Horn, et al. For multi-objective optimization is proposed NPGA the Zitzler proposed of SPEA, and practice. On the other hand, improved unmarked concept of the members of the species population, and was named on NSGA. Before the packet, all unmarked member is marshaled to a pressure in the healthy group, and each individual members of this group have the same reproductive potential. In order to maintain the diversity of the population, grouping members of the health value to be shared. Subsequently, the arrangement of another set of unmarked individual choreography, has been down, until all groups. Results, the first member of the health value, and have greater reproductive capacity than the rest of the population. Coello et al. Pareto packet over and over again repeated, so he felt that the the NSGA efficiency is not high. Clearly, a more efficient way to get the same result is very possible.As an advanced version of the NSGA, in order to improve computational efficiency, Deb et al. Introduced the NSGA-II, NSGA-II, each program must be determined that it named the program, the NSGA-II evaluation of special programs in the population around the density, in fact, this density is the average distance between two points. NSGA-II does not require external memory and other MOEAs. In addition, because it is an innovative organization, so some researchers have successfully applied to engineering problems. In this study, the robot on the mixed-mode aerial vehicles (HMAWV) is also used to optimize the structure size. 3.A case study: manipulators of HMAWVHMAW a top mechanical products in the field of construction machinery, is widely used in power industry, municipal engineering, and fire department. Its scope of work can reach a height of about 19 m. Because the operator must ensure the safety of facilities, the structural design must be absolutely reliable. In this study, an integrated design, strength analysis and structural optimization. Fig.2. Hybrid mode aerial working Fig.3. Extended status of HMAWVShown in Figure 2, HMAWV 19 parts: 1 - hydraulic foot, 2 - chassis, 3 - turret, 4 - the main hydraulic cylinders, arm 5 -, 6 - Auxiliary arm, 7 -pull rods, 8 - before support, 9 - the second arm, 10 - the second arm of the auxiliary, 11 - support, 12 - contraction of the hydraulic cylinder, 13 - the first parallel to the hydraulic cylinder, 14 - the first contraction of the arm, 15 -contraction of the hydraulic cylinder, 16 - the second contraction of arm, 17 - contraction arm, 18 - second parallel hydraulic cylinder, 19 - Operating Room. The table can be divided into two parts according to the movement: First, include 1-10 of the folded part, including 11-17 the extension of. Therefore, the mixed model table with integrated folding and extension of both worlds. When it works, hydraulic system to control the movement of each component, the main hydraulic cylinder to control the movement of the folded part. The parallel between this and the first arm and auxiliary arm movement is similar to the second arm and the second auxiliary arm to follow the same law of motion. Energy by dragging the rod to pass from the first arm to the second arm. When the contraction of the second contraction of the hydraulic cylinder control arm, the main contraction of the hydraulic cylinder control the extension of the movement. Chain to control the third contraction of the arm 13 to -18 partial control of the balance of the operating room, Figure 3 shows the conditions of the working vehicle.1.2中文翻译一个针对复杂机械结构的多目标优化集成方法（译文） 徐冰，陈南，车华军 东南大学机械工程学院，中国南京211189现在已经有人提出了一个针对复杂机械结构的多目标优化集成方法，这种方法集成了原型建模，有限元分析和优化。为了探索它相对于传统方法的优势，在混合模式高空作业车（HMAWV）上的机械手已经采用了这种优化，这样做的目的是增加其工作领域，在足够的强度前提下降低成本，将设计变量的几何尺寸，并且几何尺寸能够参数设计，NLPQL和NSGA II被综合应用去获得最佳解决方案。结果显示这种集成方法比穷举搜索算法更有效率。NSGA -可以接近全球前沿技术，而NLPQL和NSGA - II两者的相对误差是微不足道的。因此，这种集成方法是有效的，并在工程应用领域显示了其潜力。1 引言 为了提高产品的市场竞争力,结构设计、分析以及优化就像同步工程一样已经被整合进入概念发展阶段的过程。科学文献里有设计一个新产品各种各样的技术,其中计算机编程越来越流行，因为，伴随着计算机能力和软件技术革命的前进，编程的优越性已经在效率和精度上体现了出来。传统的计算机编程是这样的：首先，工程师绘制产品的草图；其次，使用计算机辅助设计(CAD) 软件建立几何模型，随后，大部分工程师将这个CAD模型导入到有限元分析工具中去评价它的结构性能，最后，由ANSYS ，MSC /NASTRAN，ABAQUS等一些商用软件来完成尺寸和和拓扑优化。在这个方向已经有许多重要的进步，一些研究人员利用国产研究工具MSC / NASTRAN去实现结构优化，Barkeret al 介绍了关于MSC /NASTRAN的二次开发，并且已经被两个实例证实了。最近，Hansen 和 Horst 根据精细的有限元模型开发了一个多级优化程序，也就是说第一步用发展找略优化拓扑参数，第二步应用MSC / NASTRAN优化模型的厚度和纵切面，不过简化了边界条件。虽然以这种方式做出了许多努力，但是由于传统优化算法的禁锢，解决方案仍然被困在现在的某个区域，并且忽视了许多非线性因素以致于这种方案还不精确。这种新奇的方法是一种同步的将有限元软件集成到优化程序的方法。它采用随机搜索算法做为优化方法,这不仅可以防止优化器被困住在当地的区域，并且可以达到全球精确的最优方案。许多优化工具已经在文学领域进行开发，CAOSS出现得比较早,它是一个模块扩展有限元程序。Bakhtiary et al 提出了CAOSS和MSC / NASTRAN之间的新接口，接着Meskeet al介绍了这个接口通往FEMsolvers，MSC/NASTRAN, MSC/Fatigue, ABAQUS, MSC.Marc 以及MSC.Patran的方式。私有软件DynOPS是作为优化工具的另外一个选择，Giger 和 Ermanni 利用DynOPS把有限元分析软件ANSYS应用到开发复合纤维增强塑料摩托车钢圈中。Hilmann介绍了一个优化软件SFE concept，这个软件被广泛用于德国的汽车行业。ISIGHT是另一个优化软件，它包括广泛的经典和非经典的优化方法,如实验设计(DOE)，近似交换技术，多标准分析和质量工程方法。Qian 和 Yuan 成功将UG, ICEM-CFD,和FLUENT集成到ISIGHT，并且实验设计(DOE)被用于设计underhood。后来，Cullimore et al.为了优化一个观测太空望远镜而将MSC / NASTRAN和 Fluent 集成到ISIGHT。尽管许多优化工具已经被广泛开发，但是对复杂机械结构的多目标优化仍然是个挑战。在这项研究中,一个完整的设计方法和多目标结构优化是先进的。用ANSYS软件和优化算法进行有限元分析被集成到一个商业优化软件ISIGHT-FD，并且详细的证实了这些集成过程。作为一个应用的例子，多目标优化的机械手得到了开发，这样做的目的是扩大其使用范围,同时在足够强度的前提下通过优化几何尺寸减轻其质量。无论是基于变化率的古典算法还是现在的进化算法都被采纳来取得最佳方案。在第二部分中, 探讨了包含有限元模型的集成程序，仿真过程,和优化算法。在第三部分中，混合模式高空作业车（HMAWV）上的机械手作为一个研究实例被提了出来。应用接触单元模拟连接，来验证有限元分析的结果，开发试验应力分析。并且采纳NLPQL和NSGA-II去优操纵宗器。比较两种算法的优化结果。而且，为了验证对最佳方案的影响，对NSGA-II的参数定义不同值。在第四部分中，做结论并且让将来的学者去研究讨论。2 并行方法的集成程序结构优化的关键是有没有能力自动生成各种设计的虚拟样机模型。为实现并行设计和优化，四个基本步骤必须验证参数化模型。 ANSYS提供了一种参数化的有language-ANSYS建模方法设计语言(APDL)，可以用来自动化相同的任务甚至建立数学模型等方面的参数。因此,自动网格文件和计算有可能定义APDL文件,并且渗碳层深度逆问题求解也可以得到分析结果。此外,运用有限元分析软件ANSYS,对运行处理模式,即图形用户接口(GUI)将不会出现并编制相应的计算程序，只是在后台运行命令。APDL文件包括设计变量,和输出文件包括约束和目标,优化控制文件仅能整合这两个文件,实现并行基于有限元分析的优化。图一阐述了同步设计和优化过程，如图所示的过程是一个循环的过程。ISIGHTFD是控制单元,它控制着有限元分析和优化的性能。在这个模拟过程中，有限元分析和优化能够在没有人工操作的情况下执行。因此,这一过程可以提高其优化效率,扩大变量的设计空间。图一 集成优化过程流程图2.1 有限元分析模型文本的编译器能够生成APDL文件,而且APDL文件可以在图形用户界面(GUI)模式或批处理模式中定义任何完成的命令。那里是一个层级的分类,即几何量是顶部的等级,然后表面,然后线,keypoint最低。因此两种建模方法可以应用于APDL文件,无论是从上到下还是从下到上。在本研究中,方法采用从下到顶部被定义的基础,因为要协调,并且他们的位置可参数化的很容易。当我们在界定了可能产生的几何元素特殊的元素类型。H-refinement和p-refinement是两种网格结构分析提炼的方法。H-refinement啮合精度提高越来越多的元素,而p-refinement啮合精度的提高增加程度的形函数的元素,但p-refinement成本更多的计算时间。h-refinement定期应用方法具有较高的求解精度。验证了该质量的元素,许多条款需要检查,他们是长宽比偏离90,在平行相对边缘的偏离度,最大值在度角而且定制的值可以被定义用户。如果没有警告和错误出现,它表明所有这些条款都满意,和计算可以开始了。当解决方案已经完成,结果即可从渗碳层深度逆问题求解,阅读和写进一个输出文件,该文件将提供约束和目标函数优化。2.2 仿真过程 仿真在计算机工作站上运行，并且要占用许多计算