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LW01-044@基于CADCAE的拼焊板桶形件冲压成形工艺设计,机械毕业设计 论文

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南京理工大学泰州科技学院 毕业设计（论文）任务书 系 部 ： 机械工程 系 专 业 ： 机械工程及自动化 学 生 姓 名： 夏正恭 学 号： 0501510142 设计 (论文 )题目 ： 基于 CAD/CAE 的 拼焊 板桶形件 冲压成形工艺设 计 起 迄 日 期 : 2009 年 3 月 9 日 6 月 14 日 设计 (论文 )地点 : 南京理工大学泰州科技学院 指 导 教 师 : 张 卫 专业 负责 人 : 龚光容 发任务书日期 : 2009 年 2 月 26 日 nts 任务书填写 要求 1毕业设计（论文）任务书由指导教师根据各课题的具体情况填写，经 学生所在专业的负责人 审查、系部领导签字后生效。此任务书应在第七学期结束前填好并发给学生； 2 任务书内容必须用黑墨水笔工整书写或按教务处统一设计的电子文档标准格式（可从教务处网页上下载）打印，不得随便涂改或潦草书写，禁止打印在其它纸上后剪贴； 3 任务书内填写的内容，必须和学生毕业设计（论文）完成的情况相一致，若有变更，应当经过所在专业及系部主管领导审批后方可重新填写； 4 任务书内有关“系部”、“专业”等名称的填写，应写中文全称，不 能写数字代码。学生的“学号”要写全号； 5 任务书内“主要参考文献”的填写，应按照国标 GB 7714 2005文后参考文献著录规则的要求书写，不能有随意性； 6 有关年月日等日期的填写，应当按照国标 GB/T 7408 2005数据元和交换格式、信息交换、日期和时间表示法规定的要求，一律用阿拉伯数字书写。如“ 2009 年 3 月 15 日”或“ 2009-03-15”。 nts 毕 业 设 计（论 文）任 务 书 1本毕业设计（论文）课题应达到的目的： 通过本课题旨在让学生了解并熟练运用有限元分析，通过对拼 焊板桶形件冲压成形工艺的研究， 探讨 拼焊板桶形 件 冲压成形工艺 ， 了解有限元分析在冲压工艺中的实际运用。 通过本课题可以培养学生解决实际问题的能力，提高学生的综合应用能力和独立工作能力，为学生最终走向工作岗位打下基础。 2本毕业设计（论文）课题任务的内容和要求（包括原始数据、技术要求、工作要求等）： 本课题首先选取了简单的轴对称件 桶形件作为研究起点，针对智能数控冲压机床对压边力控制的要求，借助 CAE 手段通过改变压边力方式和材料差厚，进行拼焊板的成形性能的有限元分析仿真，探讨拼焊板桶形件冲压成形工艺。 原 始数据： 所选的原材料为低碳钢，其它尺寸如下（ mm）： 毛坯 凸模 凹模 直径 d 直径 dp 圆角半径 rp 直径 Dd 圆角半径 rd 100 56.8 7.0 60.0 8.0 采用的拼焊板由两块大小相等（半径为 50mm）、厚度分别为 0.8mm 和 1.6mm 的半圆形板料焊接而成。 技术要求 : 取凸模的模拟运动速度为 2000mm/s。行程为 20mm，凹模、凸模和板料间及压边圈和板料间的摩擦系数都为 0.125，通过实验对在范围 150 40（ kn）内压边力进行选择，通过观察其 FLD 图最终确定了选择压边力 工作要 求： （ 1）文献查阅有关板材冲压和有限元方面的资料 （ 2）建立拼焊板桶形件凸凹模 CAD 模型； （ 3）对拼焊板桶形件冲压成形过程借助 dynaform 软件进行 CAE 有限元仿真分析； （ 4）按要求提供各种设计文档，并完成毕业论文。 nts 毕 业 设 计（论 文）任 务 书 3对本毕业设计（论文）课题成果的要求包括毕业设计论文、图表、实物样品等： （ 1） 拼焊板 桶 形件 的有限元分 析 数据 （ 2） 毕业设计论文 4主要参考文献： 1 姜奎华 . 冲压工艺与模具设计 M.北京 ： 机械工业出版社 ,2002. 2 胡世光 . 板料冷压成形原理 M.北京 ： 国防工业出版社 ,1979. 3 刘建祥，陈炜，吕盾，等 .应用变压边力控制技术改善拼焊板的成形性能 J.模具工业， 2007， 33(8)： 20-24. 4 李硕本 . 冲压工艺理论 与 新技术 M. 北京：机械工业出版社 .2002. 5 吴诗惇 . 冲压工艺及模具设计 M. 北京：西北工业大学出版社 .2002. 6 姜雷 ,陈君若 ,沈选举 ,孙东明 . 圆筒形零件拉深压边力的数值模拟 J.机械 .2004， 22(5) ： 32-35. 7 S.Thiruvarudchelvan, F.W.Travis et al. On the deep drawing of cups with punch and blank-holder forces proportional to a hydraulic pressureJ. Materials Processing Technology, 2000(88):92-93. 8 谢晖 ， 杨旭静 ， 成艾国 ， 李光耀 ， 钟志华 . 计算机仿真中板料冲压成形压边力的优化 J.中国机械工程 ， 2002， (11):1910-1914. 9 张士宏 ， 许 沂 ，王忠堂 ， 等 .拼焊板料冲压成形技术（） J.金属成形工艺 2001，19.20（ 4）： 1-3. 10 Leonid BShulkin, Ronald et al. Blank holder force(BHF) control in Viscous pressure forming (VOF) of sheet MetalJ. Materials Processing Technology, 2000:97-99. nts 毕 业 设 计（论 文）任 务 书 5本毕业设计（论文）课题工作进度计划： 起 迄 日 期 工 作 内 容 2009 年 3 月 9 日 3 月 29 日 3 月 30 日 4 月 12 日 4 月 13 日 4 月 27 日 4 月 28 日 5 月 16 日 5 月 17 日 5 月 31 日 6 月 1 日 6 月 14 日 完成 外文资料翻译 、 文献综述 和 开题报告 完成 基于有限元分析的 拼焊板 桶 形 件冲压成形工艺研究 总体方案设计 。 使用 Pro/E 软件完成对 拼焊板 桶 形件的凸模、凹模及板料模型进行 CAD 建模 选取不同的参数 使用 DYNAFORM 软件对 拼焊板桶形件成形性能 进行 有限元分析 讨论 。 完成毕业论文 并 准备毕业答辩 论文 答辩 所在专业审查意见： 负责人： 年 月 日 系 部 意见： 系 部主任 ： 年 月 日 nts南京理工大学泰州科技学院 本科生毕业设计（论文）选题、审题表 系 部 机械工程系 指导 教师 姓 名 张卫 专业技术职 务 高级工程师 课题名称 基于 CAD/CAE 的 拼焊板桶形 件冲压成形工艺研究 适用专业 机械工程及自动化 课题性质 A B C D E 课题来源 A B C D 课题预计 工作量大小 大 适中 小 课题预计 难易程度 难 适中 易 课题简介 桶形 件 由于属于轴对称件，是研究复杂几何形状件的 冲压成形 工艺的基础。本课题首先选 取了简单的轴对称件 桶形 件 作为研究起点，针对智能数控冲压机床对压边力控制的要求，借助 CAE 手段通过改变压边力方式 和材料差厚， 进行 拼焊板 的成形 性能的有限元分析仿真，探讨 拼焊板桶形 件 冲压成形工艺。 课题应完成的任务和对学生的要求 1 论文要求： （ 1）文献查阅有关 板材冲压和有限元 方面 的 资料 （ 2） 拼焊板桶形 件 CAD 模型建立 ； （ 3） 拼焊板桶形 件冲压成形 CAE 有限元分析 ； （ 3）仿真调试； （ 4）按要求提供各种设计文档 2要求学生具备机械设计、 CAD 等方面的基础知识。 所在专业审定意见： 专业负责人 (签名 )： 年 月 日 本课题由 同学选定，学号： 注： 1该表由指导教师填写，经所在专业负责人签名后生效，作为该专业学生毕业设计（论文）选题使用； 2有关内容的填写见背面的 填表说明 ，并在表中相应栏内打“ ”； 3课题一旦被学生选定，此表须放在学生“毕业设计（论文）资料袋”中存档。 nts 填 表 说 明 1 该表的填写只针对 1 名学生做毕业设计（论文）时选择使用，如同一课题由 2名及 2 名以上同学选择，应在申报课题的名称上加以区别（加副标题），并且在“设计（论文）要求”一栏中说明。 2 “ 课题性质” 一栏： A产品设计； B工程技术研究； C软件开发； D研究论文或调研报告 ； E其它。 3 “课题来源” 一栏： A自然（社会）科学基金与省（部）、市级以上科研课题； B企、事业单位委托课题； C校、院（系）级基金课题； D自拟课题。 4 “课题简介” 一栏： 主要指该课题的背景介绍、理论意义或实用价值。 nts南京理工大学泰州科技学院 学生毕业设计（论文）中期检查表 学生姓名 夏正恭 学 号 0501510142 指导教师 张卫 选题情况 课题名称 基于 CAD/CAE 的拼焊板桶形件冲压成形工艺 设计 难易程度 偏难 适中 偏易 工作量 较大 合理 较小 符合规范化的要求 任务书 有 无 开题报告 有 无 外文翻译质量 优 良 中 差 学习态度、出勤情况 好 一般 差 工作进度 快 按计划进行 慢 中期工作汇报及解答问题情况 优 良 中 差 中期成绩评定： 良 所在专业 意见： 负责人： 2009 年 4 月 3 日 nts57 1 I Intelligent Design Architecture for Process Control of Deep-Drawing K. Manabe*, H. Koyama*, K. Katoh* and S. Yoshihara* *Tokyo Metropolitan University Department of Mechanical Engineering, Hachioji-shi, Tokyo 192-0397, Japan *Integrated Systems Japan, Ltd. Asahi Bank Gotanda Bldg. 1-23-9 Nishi-gotanda, Shinagawa-ku, Tokyo 14 1-003 1, Japan *Tokyo National College of Technology Dept. Mechanical Engineering, Hachioji-shi, Tokyo 193-86 10, Japan ABSTRACT A concept of design architecture with a database for an intelligent sheet metal forming system was proposed to enable designing of a process control system without experts who are skilled and experienced in the forming process. In this study, the proposed architecture was applied to the variable blank holding force (BHF) control technique for circular-cup deep-drawing. The system is available for three objective functions which are typical process requirements, cup wall uniformity, cup height improvement and energy saving. The availability of this design architecture is confirmed by experiments on aluminum alloy sheets. INTRODUCTION Several studies on the optimization of process control in metal forming have been performed in an approach toward intellectualization. For sheet stamping operations, intelligent deep-drawing techniques have been developed to date. One technique is an adaptive control method by means of blank holding force (BHF) with fuzzy inference for circular-cup deep-drawingl. Another one is a control approach based on a plastic deformation model involving the material and friction identification process with an artificial neural network (ANN)2. Despite their excellent advantages, each control system requires very extensive time and labor for the design and development process, and above all, the design engineer has to be a knowledge expert as well as skilled and experienced engineer on the forming process techniques, or else, the assistance of a craftsman would be essential. Therefore, it is necessary to establish a new concept for process design architecture which obviates the requirement for an expert. In general, the forming cell and system must be efficiently designed during process design and process control. In the former system, as shown in Fig. 1 (left), the expert plays a number of roles as the core. Fig. 1 A new intelligent approach for various design phases on metal forming processes 0-7803-5489-3/99/$10.00 01999 IEEE. nts572 He also acquires the required experience and transfers the knowledge to inexperienced engineers. The number of experts has been gradually decreasing over the years. Thus, in the future system, the process conditions must be automatically optimized without the aid of an expert. The purpose of this study is to enable freedom from the dependency on engineering experts in the design phases of process planning and control design and to develop an intelligent design architecture for deep-drawing process control without the aid of a knowledge expert. OUTLINE OF A NEW INTELLIGENT PROCESS DESIGN AND ITS SYSTEM ARCHITECTURE Our concept shown in Fig. 1 (right) involves the replacement of the brain functions of an expert by a processor which contains an analyzer, database and knowledge base. The processor can design and control the process according to a suitable set of rules and algorithm from the database and knowledge base, and stores the sensing information from a forming cell during the process, which is similar to the experience of an expert. In other words, it can grow by acquiring experience in the same: manner as an expert. Hence, the proposed system is able to automatically optimize the process and can be (operated without any aid from an expert. Figure 2 shows the outline of the system architecture based on the above concept. It can be broadly divided into two parts. One is a processor and another one is a forming cell and system. The forming cell has several sensors for supplying process information to the processor, and aho has actuators to implement the commands from the processor. The processor consists of a database, Etnowledge base and an analyzer (commercial control design support tool; MatrixX). The database and knowledge base contain the process information under various conditions and the methodology for designing the process, respectively. The processor is capable of not only designing the process using the database and knowledge base but also identifying the material properties of the workpiece and control actuator using sensing information from the sensors. In addition, the system can handle a variety of workpieces as well as the change of workpiece material, tooling conditions and lubricating conditions, by utilizing the database and knowledge base. APPLICATION OF THE ARCHITECTURE TO DEEP-DRAWING PROCESS In this study, the circular-cup deep-drawing problem is adopted as a fundamental and important example of the sheet metal forming process. In the deep-drawing process, the forming limit is mainly governed by the fracture at the punch shoulder and the wrinkle at the flange part. Although it is essential to apply the BHF to avoid wrinkles, excessive BHF causes fractures. Therefore, the appropriate amount of BHF is required to carry out the process successfdly. So the new design architecture is applied for the adaptive control of BHF in the deep-drawing process in order to verify the availability of the architecture. Figure 3 shows the design system architecture for an intelligent metal forming process with a database. In the system, hzzy inference was chosen as an AI tool for process control design. Processor Forming cell and system Process design Process control Fig. 2 A concept of intelligent metal forming cell with database nts573 Process DB at const. BHF Processor Database (Various shapes, conditions) Mini Database (Target shape, condition) fuzzy rule function F Process design Process control Fig. 3 System architecture of intelligent forming process for deep-drawing process The evaluation functions should not be influenced by the blank material, tooling conditions, environmental conditions and other factors. For this reason, evaluation functions Cp and $, obtained from the punch stroke curve and y and yf, from maximum apparent blank thickness curve are used. The evaluation function Cp is the difference between the actual punch stroke curve and the ideal curve, which can be obtained geometrically by assuming uniform wall thickness. I$ is the differential coefficient of + by blank reduction ratio ADR*. A combination of Cp and I$ is used for fracture estimation. The evaluation function r is the blank holder displacement which is equal to blank thickness at the flange edge and is used instead of the wall thickness distribution. In the same manner as Cp, a combination of y and r is used to evaluate wrinkle behavior. A constraint function x is defined as the differential coefficient of the punch load curve to evaluate the progress of the process. The database in this study is composed of four kinds of process variables, punch stroke, punch load, maximum apparent thickness, and ADR*. The blank reduction ratio ADR* can be obtained from the displacement of the flange edge and is given by S -DR* =- Ro where & is the initial blank radius and s is the displacement of the flange edge.These process data are utilized to design the sets of appropriate membership functions of the evaluation functions so that they have to be accumulated under various material and process conditions (material properties, tooling condition, lubrication condition, ambient condition among others). In this proposed architecture, three objective functions can be designed. The first is the improvement of the cup height, which can be achieved by applying the maximum BHF below the fracture limit. The second is process energy savings by implementation of the minimum BHF beyond the wrinkle limit. The third is for the wall thickness uniformity, whose control scheme can be achieved by a combination of the above two objective functions. ntsf :r Unsucessful conditions Progress of proces Fig. 4 Requirement of process information contained in the database f Fig. 5 Sets of input membership functions 574 Table 1 If-then rule of 9, Q and ABHF Then(ABHF) ABHF= ABHFss -I- if(, ) is Small and is Small (I is Small and (I is Large I ABHF=ABHFL (I is Large and is Small is Large and is Large t ABHF= ABHFLL ABHF= ABHFLs A BHF A BHF& BHF A BHF -1.0 -0.6 -0.2 0.2 0.6 1.0 A BHF / kN Fig. 6 A set of output membership functions FUZZY MODEL Application of the fuzzy model provides a suitable and easy way to optimize process control because the deep-drawing process is not only unsteady and complicated but also has nonlinear forming characteristics. The sets of membership functions used for the antecedent of the If-then rules are designed through the database. The database must contain at least two typical conditions of the constant BHF. One is a high BHF condition which causes fracture and another one is a low BHF condition which leads to wrinkling as shown in Fig. 4. Two membership functions related to 9 are built from the process data as mentioned in the previous section. The latter data create two membership functions in relation to y. In the present study, only two sets of membership functions concerned with $ and were employed because the objective function is the improvement of cup height as described above. Two maximum values and qb in Fig. 5 should correspond to the state of fracture. Hence each value was decided on the basis of the maximum value retrieved from the database of fracture limit conditions. Meanwhile, & and (fa were decided by substituting the minimum value stored in the database in similar to Q and (p. Figure 6 shows the set of membership functions used for the consequent of If-then rule. This part was decided with the assistance of an expert with experience resulting from trial and error in the previous work 4. However, the use of this new simplified set of membership functions does not require any experience so that the designer and machine operator need not be skilled and experienced. The initial range of each membership function in Fig.6 can be automatically designed via this system. They only have to provide the multiplier to the value of the system output (ABHF),whose value was 0.2, due to the dependency on the forming cell used. Table 1 shows the If-then rules for BHF control. Figure 7 shows the fizzy inference for ABHF used in this study. Although the max-min-rule is the most common inference rule, larger membership functions are omitted, when the min-operator is used. However, it is desirable that both membership functions be considered. Therefore, in this work, the areas of the membership functions are used desspite of the use of the min-operator as shown in Fig. 7. Fuzzy outputs of individual fuzzy rules are combined using the max-operator and the centroid of the area is the output. nts575 Yield Stress Tensile Strength os I Nmm- oB I Nmm- LL LStSL ss F value Elongation I Nmm- R value N value ABHF 4 Fig. 7 Fuzzy inference model for ABHF Table 2 Material properties of blank used 117 264 398 30.1 0.28 0.6 Punch Speed BHF 5 mm/min constant 0.5-50 kN variable Punch shoulder radius rp / mm Punch diameter D, I mm Lubrication I Lubricating oil (2 18 mms-) 4 33 Die shoulder radius rd I mm 13 DR 1.98 Die diameter Dd / mm EXPERIMENT Material Used and Experimental Conditions Aluminum alloy sheet metal (A5 182-0) of thickness 1 .Omm was used in the deep-drawing experiment. The material properties are listed in Table 2. The deep-drawing system used is capable of computerized control of BHF and the punch speed during the process 3. The system has several sensors: punch stroke, punch load, BHF, radial drawing displacement of the blank flange which was sensed by a displacement transducer and blank holder displacement by an eddy current displacement transducer. Tables 3 and 4 show the experimental conditions and tooling conditions, respectively. 301 I 1 I I ly I I I I I I I I I I I I 1,yl I I I I I I I I I I I I 23.0 I I I I I I I I I 1 I I I I I I I I I - b I I I lj - 100% j 101.25% I 36.5 z Y 20 5 m .p- 15 m 0 1,; j i at cbnstant BHF j 4 U -.- I 0 ll I I I i I I I i I I I I i I I I I i T I I I i I I I I i I I I I : IDR: 1.98 20.0 11111 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 const. BHF variable BHF Fig. 9 Comparison of cup height between const. and variable BHF conditions. ADR* BHF Type Fig. 8 Punch load and controlled BHF curves during the process nts576 Experimental Procedure The first step in the design process is to construct the database from the results of the constant BHF test. In the present architecture, the process information for the fracture and winkle limit BHF conditions are essential. However, since this study deals with the improvement of the cup height as the objective function to verify the effectiveness of the design system architecture, process information related to fracture limit BHF condition was collected and stored in the database. CONSTANT BHF DEEP-DRAWING TEST FUZZY CONTROLLED VARIABLE BHF DEEP-DRAWINGTEST The variable BHF deep-drawing test with fuzzy control was conducted on the basis of the above objective function. The details of the procedure are as follows. First, membership functions are produced by usng a database constructed from the constant BHF test. Second, initial BHF, blank geometry and punch speed are input into the processor and then the die descends at a constant speed. The BHF is automatically controlled in a closed loop to satis the objective function by the obtained fuzzy rule. In this study the initial BHF is set to 1 .OW. For the objective function of the highest cup, the processor basically controls BHF to increase it to the maximum possible value to obtain the highest drawn cup. When the evaluation function indicates a high possibility of fracture, then the BHF can be controlled to decrease it in order to avoid fracture. On the contrary, when the evaluation function shows enough allowance to fracture, then the BHF can be increased. RESULTS AND DISCUSSION Figure 8 shows the experimental curve