板料成形工艺智能设计关键技术研究
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摘要
板料成形广泛应用于汽车、航空、航天等领域,在国民经济中占有重要的地位。对于板料成形而言,板料成形工艺设计是关键。板料成形工艺设计过程不仅是科学更是艺术,包含着人类的创造力和直观性的经验,传统上需要设计人员根据书本上的知识和直观经验来制定。而正是由于板料成形工艺设计过程存在着信息缺失、信息过饱和以及信息不确定性,导致了目前大多数的板料成形工艺设计系统在应用上存在限制。因此,如何解决板料成形工艺设计过程中存在的不确定和非线性问题是学术界和工业界的迫切需求。仿生智能与生物中的一些部分信息处理系统相对应,具有在不确定的环境中进行逻辑推理以及联想学习的能力,能够解决复杂系统中带有不确定因素的建模和优化问题,这与板料冲压成形工艺设计中的不确定性、不完整性和非线性是相对的。同时对提高板料成形工艺设计的智能化、自动化水平具有重要的理论和工程意义。
本文以仿生智能技术中的模糊理论和免疫算法为基础,开展了板料成形工艺智能设计理论以及关键技术的研究。建立了基于模糊综合评价的板料成形工艺性评判系统;研究了基于模糊的板料成形工艺设计,建立了筒形件模糊板料成形工艺设计系统,模拟了设计人员的设计流程:提出了板料成形工艺参数的模糊理论算法;研究了模糊聚类算法,并同统计学理论结合,建立了弯曲回弹模糊聚类知识分析系统;研究了翻边毛坯模糊设计方法,建立了翻边毛坯模糊设计系统;研究了免疫克隆算法,将其同近似模型相结合,最后构建了基于免疫克隆算法的板料成形多目标工艺优化方法。
针对传统板料冲压成形工艺设计流程中的关键问题,研究了板料成形工艺设计过程中的经验性和不确定性,将模糊理论引入板料工艺设计,模拟了人类工程师的板料成形工艺设计的思维。
冲压件的工艺性判断是冲压工艺设计中极其重要的一步。由于冲压件受多种因素的影响,为了确定冲压件的工艺性,专家经验知识必须被考虑。模糊综合评价作为一种对受多种因素影响的事物做出全面评价的一种十分有效的多因素决策方法,能够结合冲压专家知识解决此类问题。首先,对影响板料冲压成形工艺性判断因素进行筛选,选用形状几何尺寸、精度以及材料性能三因素作为第一级:将形状几何因素进一步的分为形状复杂程度、工件最大距离以及工具最大距离与工件高度比值三种影响因素;同时,根据各个因素对冲压件工艺性的影响程度建立了隶属度函数;建立了板料冲压成形工艺评价目标集。在对冲压工艺性影响因素评价的基础上,采用多级模糊综合判断算法与最大一最小算法对冲压工艺性进行评价,并编写了算法。最后以离合器盖为例,对其进行了冲压工艺性评价。根据冲压件的工艺参数和各个阶段主要影响因素分别建立了评价矩阵和权重集。根据两次评价结果发现,隶属度函数以及权重的获得对板料冲压成形工艺性的评价结果具有重大影响。
由于冲压工艺设计方法缺少高度自动化设计软件,设计人员还是主要的依靠本身的经验,导致了冲压件从设计、生产、调试需要花费大量的时间,所以本文将模糊理论引入传统的模具设计过程中,模拟工程师的设计流程。建立了拉深工艺设计系统,主要包括输入输出模块、知识库模块、工艺设计模块。该系统首先根据面向对象的方法建立了冲压知识表达模型,然后参考模糊理论所提供的将知识库向非线性映射转换的工具,建立了设计过程的智能调整模型。最后,以筒形件为例,展示了整个设计过程,系统结果合理有效。
传统的模具设计涉及大量的工艺参数,但由于手册上的工艺参数只是在单一实验条件下获得的,其泛化性能具有一定的局限性,导致了板料成形工艺设计过程中需要大量的工程经验知识。本文将工艺参数结合模糊理论,提出了两种工艺参数的模糊修正算法。第一种,利用模糊系统计算模糊修正系数,将其同传统的工艺参数相乘,获得修正的工艺参数:第二种将目前的工艺参数同影响因素一起嵌入模糊系统,进行理论修正计算,获得修正的工艺参数。最后,以拉深系数为例,展示了构建过程。
在塑性加工领域,大量的实验数据和有限元模拟数据充斥在书本、实验报告、工程师的经验中,使大量的工作处于离散和重复的状态,为了从各种工艺数据中寻找模式、提取隐含的、潜在的知识,引入了模具聚类方法,结合统计学理论,针对板料弯曲回弹的进行了模糊聚类分析研究。首先,以低碳钢弯曲回弹为研究对象,建立了弯曲回弹模糊聚类知识分析模型;然后,对模糊聚类算法进行了研究,构建了弯曲回弹模糊聚类系统。接着,进行了弯曲回弹模糊聚类知识分析,获得了弯曲回弹聚类模型。以材料性能、弯曲角、相对弯曲半径为参数对构建的回弹聚类模型进行了进一步的检验和测试,预测结果同真实回弹结果符合良好,证明其有效性和可靠性。在进行镁合金板料弯曲回弹试验的基础上,将模糊聚类知识分析引入镁合金板料弯曲回弹分析,提出了镁合金板料的弯曲回弹模糊聚类知识分析,分别构建了镁合金板料弯曲回弹隶属度函数和弯曲回弹模糊聚类分析模型,有效地进行了镁合金板料弯曲回弹模糊聚类知识分析。
毛坯设计是板料工艺设计中的关键问题,本文在研究翻边成形的应力状态分类的基础上,总结了翻边类型分类组合。根据翻边类型分类组合,提出了组合式翻边毛坯模糊设计方法,分别构建了压缩类翻边毛坯模糊设计系统、伸长类翻边毛坯模糊设计系统、弯曲类翻边毛坯模糊设计系统。为了构建翻边毛坯模糊设计系统,本文提出了基于Table Look-up Scheme板料成形工艺模糊系统构建方法。针对翻边毛坯设计,将翻边零件边界和毛坯边界进行了离散,构建了基于TableLook-up Scheme的翻边毛坯设计系统的输入一输出数据集。然后,研究了TableLook-up Scheme的知识库构建方法,将输入—输出空间进行了模糊划分建立了隶属度函数,根据输入—输出数据集构建了IF—THEN规则,并利用规则强度,解决了规则冲突的问题。然后,选用带有乘积推理机、单值模糊器、中心平均解模糊器,构建了基于Table Look-up Scheme的翻边毛坯模糊设计系统。由于存在隶属度函数获取的主观性、规则冲突及获取等问题,引入了自适应模糊系统。然后,对翻边毛坯自适应模糊设计系统的模糊空间的划分和隶属度函数的形式的影响作了研究,得出了隶属度函数选择高斯函数形式较好,考虑到计算效率和精度,模糊空间划分为3～5份比较合适。以内曲翻边为例,检验了翻边毛坯自适应模糊设计系统的输出。本文最后以S形翻边为例,将其输入翻边毛坯模糊设计系统,从而获得了毛坯形状,并进行了试验验证,成形结果良好。
将免疫克隆算法与近似模型构建方法相结合,提出了基于免疫克隆算法的板料成形工艺优化方法。研究了免疫克隆算法的原理与构建,以VC++为平台编写了克隆算子、变异算子、选择算子,实现了免疫克隆算法。鉴于板料成形问题的复杂性和非线性,导致了其数学模型构建的困难,利用近似模型构建了板料成形工艺多目标优化模型。首先,采用数字模拟的结果构建了响应面空间点,利用二乘法获得了响应面函数,并编写了计算结果接口与响应面函数的求解程序。然后,建立了多目标优化模型,采用免疫克隆算法对其进行优化求解。最后,采用有限元法对最优解进行了精确分析和验证。以内曲翻边为例,建立了起皱和厚度变化的优化目标函数。对免疫克隆算法进行了求解,获得了良好的优化结果。
Sheet metal forming is widely used in automobile, ship-building, aerospace etc. It plays an important part in national economy. The key of sheet metal forming is the forming process planning. Not only is the sheet metal forming process planning scientific, but it is also artistic. The process planning of sheet metal forming contains human creative power and intuitive experience. Traditionally, the forming process planning was designed by engineer according to book knowledge and intuitive experience. And because of that, it led to the restrictions for the application of sheet metal forming process planning systems. The most important causes of uncertainty in the sheet metal forming process planning are lack of information, abundance of information, and ambiguity. Therefore, the effective handling of the uncertainty and nonlinearity constitutes the most urgent problem for the industry and academic world. Bionic intelligence is partly corresponding to the biological information processing system. It has the power of logical reasoning and associative learning for uncertainty and imprecise factors. In the complex system, it can deal with the modeling or optimization problem, which was constituted by the uncertainty factors. Then, in this paper, the bionic intelligence is introduced to solve the uncertainty, imperfection, nonlinearity problems of the sheet metal forming process planning. Not only will the application of improve the intelligent automation of sheet metal forming process planning, but it is also of great significance in theory and in practice.
In this dissertation, the bionic intelligent design theory for sheet metal forming process planning and the key technologies based on the fuzzy theory and immune algorithm of bionic intelligence was studied. The fuzzy synthetic evaluation method was directly introduced to construct the stamped parts forming performance evaluation system, which was used to evaluate the forming performance of the stamped parts. The sheet metal forming process planning system of drawing parts was constituted based on fuzzy theory, and it can simulate the design flow of human being. The calculated algorithm of sheet metal forming technological parameter was proposed. On the basis of fuzzy clustering and statistical theory, the fuzzy clustering knowledge analysis system for springback was built up. The techniques of fuzzy system theory were directly introduced to the blank design of sheet metal forming. And then, the flanging blank fuzzy design system was present. The immune clone algorithm was researched based on immune theory, and the metamodeling was established in the flanging of sheet metal forming, and the process is optimized by the immune clone algorithm.
Due to the vagueness and uncertainty in the sheet metal forming process planning, the fuzzy theory was introduced to this field in this paper, which was a special tool that can simulate the design process of human being.
Evaluating the stamping performance is a key step in sheet metal forming process planning, which is affected by several factors. In order to get the stamping performance, the knowledge of experts should be considered. Fuzzy synthetic evaluation is an effective decision-making method in the comprehensive evaluation of things affected by multiple factors, and can deal with uncertainty problem with domain expert knowledge. Firstly, the influencing factors were selected by the importance of factors. Shape complexity factors, material performance factors, precision factors were selected to establish the first level influencing factor set. Shape complexity factors could be separated into a triple including geometry factor, maximum projection distance factor between two points in XY plane, the ratio factor between height in the Z direction and maximum projection distance between two points in XY plane. The membership functions of the influencing factors were established according to the different effects of each factor. And then, the evaluation set was built based on the evaluation results of the forming performance. The multi-grade Fuzzy synthetic evaluation algorithm for the stamped part was developed. Finally, the forming performance of a typical stamped part was evaluated based on the developed fuzzy synthetic evaluation model, and the perfect result was achieved. According to the result of the evaluation, the membership function and weight set weighed with the evaluation of the stamped parts.
As well known, stamping process design involves lots of empirical knowledge, which prolongs the cycle of design and manufacturing, limits the competitiveness of enterprises. With the development of computer technologies, CAD/CAM/CAE technologies have been widely applied to the design of stamping processes and dies, but it still needs a large number of engineers' experiences. Fuzzy theory was introduced into the process of traditional stamping process design, and a drawing process design system was established, which mainly includes input and output module, knowledge data-base module, process design module. First, according to the object-oriented method, the representation model of stamping knowledge was established. Then, referred to the tool provided by the fuzzy theory converting knowledge data-base to non-linear mapping, the intelligent adjustment model of design process was established. Finally, a typical part was taken as an example to demonstrate the running process of the system, and the result showed that the system is effective.
The traditional sheet metal forming process planning needs a gear mount of parameters. The process parameters can be found in the compendium, which was only built up on simple experiment condition. So, the generalization capacity of process parameters has some limitations, which led to process parameters limitations. For that reason, huge amounts of experiential knowledge should be considered in the sheet metal forming process planning. The algorithm for process parameter modification was developed based on fuzzy theory. One is fuzzy modified coefficient, which was used to multiply with classic process parameters in order to obtain modified process parameters. Another is about modified process parameters, which was calculated from the fuzzy system embedded with classic process parameters and influencing factors. At last, the effectiveness of process parameter modification for drawing rate was validated, and the calculating process was demonstrated.
In the industrial domain of plastic, there is mass of data of experiments and FEA simulation existed in books, test report, engineer experience, and the data is in the state of discrete. In order to discover the implicit and potential pattern or knowledge, the fuzzy clustering method based on statistic theory was introduced to the springback of sheet metal forming. The springback knowledge analysis model for sheet metal forming was studied firstly. And then, the algorithm for fuzzy clustering was researched in order to establish the fuzzy clustering system for spingback of sheet metal forming. After that, the fuzzy clustering model of spingback was obtained after the fuzzy clustering knowledge analysis, and the effectiveness and accuracy of the proposed model and the developed program for springback fuzzy clustering were validated. On the basis of the research of the springback experiments of Mg alloy plate, the fuzzy clustering method was directly introduced to the springback of Mg alloy plate, and the fuzzy clustering knowledge analysis for Mg alloy plate springback was proposed. The membership function and fuzzy clustering model of Mg alloy plate springback were established to get the fuzzy clustering model of Mg alloy plate. The forecasting result of fuzzy clustering model of Mg alloy plate springback is effective and accuracy.
How to design blank shape is the key problem of sheet metal forming. The fundamentals of flanging process were studied deeply, and the new flanging groups were presented. According to the flanging groups, the framework and function of combined blank fuzzy design system of flanging was developed, including straight flanging blank fuzzy design system, stretch flanging blank fuzzy design system and shrink flanging blank fuzzy design system. In order to construct the flanging blank fuzzy design system, the method of Table Look-up Scheme for sheet metal forming process planning was presented. The borders of the flanging part and the blank were separated to construct input-output data set for Table Look-up Scheme method. On the base of the research of Table Look-up Scheme method for knowledge base, the input-output space was separated in order to construct membership function of process variable. The input-output data was used to establish the IF-THEN rules. The problem of rules conflict was solved reliable by rule intensity. After that, the flanging blank fuzzy design system based on Table Look-up Scheme was constructed by product inference engine, singletom fuzzifier and center average defuzzifier. Due to the subjectivity of membership function, rule conflict and rule procurement, the adaptive fuzzy system for flanging blank fuzzy design was described. The influence of separating number of fuzzy space and the shape of membership function was studied. The Gaussian membership function is more suitable for the adaptive fuzzy system for flanging blank fuzzy design than the other types membership function. Fuzzy space would be divided into 3 to 5 parts in the term of computational efficiency and accuracy. The stretch flanging part was taken as an example to demonstrate the running result of the system. With the applications to the reverse flanging part, the effectiveness and accuracy of the blank design capacity of the system was validated by the experiments.
To combine the immune clone algorithm and metamodeling method for sheet metal forming optimization, a method for sheet metal forming optimization based on the immune clone algorithm was developed. The mechanism and framework of the immune clone algorithm were studied, such as clone operator, mutate operator and select operator. The immune clone algorithm was programmed by VC++. Because of the complexity and nonlinear of sheet metal forming, it is difficult to establish the model of sheet metal forming. So, in the dissertation, the metamodeling method was used to construct the multi-objective optimization model of sheet metal forming. Firstly, the design results based on numerical simulations were used to construct response surface functions by least square method in order to establish the multi-objective optimization model of sheet metal forming. Secondly, optimal solutions were gained from the optimization of response surface functions by the immune clone algorithm. Lastly, the optimal solutions from immune clone algorithm were verified by finite element analysis. By taking of the stretch flanging part as an example, the multio-bjective optimization design model consistent with the wrinkle and thickness was constructed. The immune algorithm was used to solve the multi-objective optimization design model and the validity and reliability of optimal solution was verified by numerical analysis of the forming process.
本文以仿生智能技术中的模糊理论和免疫算法为基础,开展了板料成形工艺智能设计理论以及关键技术的研究。建立了基于模糊综合评价的板料成形工艺性评判系统;研究了基于模糊的板料成形工艺设计,建立了筒形件模糊板料成形工艺设计系统,模拟了设计人员的设计流程:提出了板料成形工艺参数的模糊理论算法;研究了模糊聚类算法,并同统计学理论结合,建立了弯曲回弹模糊聚类知识分析系统;研究了翻边毛坯模糊设计方法,建立了翻边毛坯模糊设计系统;研究了免疫克隆算法,将其同近似模型相结合,最后构建了基于免疫克隆算法的板料成形多目标工艺优化方法。
针对传统板料冲压成形工艺设计流程中的关键问题,研究了板料成形工艺设计过程中的经验性和不确定性,将模糊理论引入板料工艺设计,模拟了人类工程师的板料成形工艺设计的思维。
冲压件的工艺性判断是冲压工艺设计中极其重要的一步。由于冲压件受多种因素的影响,为了确定冲压件的工艺性,专家经验知识必须被考虑。模糊综合评价作为一种对受多种因素影响的事物做出全面评价的一种十分有效的多因素决策方法,能够结合冲压专家知识解决此类问题。首先,对影响板料冲压成形工艺性判断因素进行筛选,选用形状几何尺寸、精度以及材料性能三因素作为第一级:将形状几何因素进一步的分为形状复杂程度、工件最大距离以及工具最大距离与工件高度比值三种影响因素;同时,根据各个因素对冲压件工艺性的影响程度建立了隶属度函数;建立了板料冲压成形工艺评价目标集。在对冲压工艺性影响因素评价的基础上,采用多级模糊综合判断算法与最大一最小算法对冲压工艺性进行评价,并编写了算法。最后以离合器盖为例,对其进行了冲压工艺性评价。根据冲压件的工艺参数和各个阶段主要影响因素分别建立了评价矩阵和权重集。根据两次评价结果发现,隶属度函数以及权重的获得对板料冲压成形工艺性的评价结果具有重大影响。
由于冲压工艺设计方法缺少高度自动化设计软件,设计人员还是主要的依靠本身的经验,导致了冲压件从设计、生产、调试需要花费大量的时间,所以本文将模糊理论引入传统的模具设计过程中,模拟工程师的设计流程。建立了拉深工艺设计系统,主要包括输入输出模块、知识库模块、工艺设计模块。该系统首先根据面向对象的方法建立了冲压知识表达模型,然后参考模糊理论所提供的将知识库向非线性映射转换的工具,建立了设计过程的智能调整模型。最后,以筒形件为例,展示了整个设计过程,系统结果合理有效。
传统的模具设计涉及大量的工艺参数,但由于手册上的工艺参数只是在单一实验条件下获得的,其泛化性能具有一定的局限性,导致了板料成形工艺设计过程中需要大量的工程经验知识。本文将工艺参数结合模糊理论,提出了两种工艺参数的模糊修正算法。第一种,利用模糊系统计算模糊修正系数,将其同传统的工艺参数相乘,获得修正的工艺参数:第二种将目前的工艺参数同影响因素一起嵌入模糊系统,进行理论修正计算,获得修正的工艺参数。最后,以拉深系数为例,展示了构建过程。
在塑性加工领域,大量的实验数据和有限元模拟数据充斥在书本、实验报告、工程师的经验中,使大量的工作处于离散和重复的状态,为了从各种工艺数据中寻找模式、提取隐含的、潜在的知识,引入了模具聚类方法,结合统计学理论,针对板料弯曲回弹的进行了模糊聚类分析研究。首先,以低碳钢弯曲回弹为研究对象,建立了弯曲回弹模糊聚类知识分析模型;然后,对模糊聚类算法进行了研究,构建了弯曲回弹模糊聚类系统。接着,进行了弯曲回弹模糊聚类知识分析,获得了弯曲回弹聚类模型。以材料性能、弯曲角、相对弯曲半径为参数对构建的回弹聚类模型进行了进一步的检验和测试,预测结果同真实回弹结果符合良好,证明其有效性和可靠性。在进行镁合金板料弯曲回弹试验的基础上,将模糊聚类知识分析引入镁合金板料弯曲回弹分析,提出了镁合金板料的弯曲回弹模糊聚类知识分析,分别构建了镁合金板料弯曲回弹隶属度函数和弯曲回弹模糊聚类分析模型,有效地进行了镁合金板料弯曲回弹模糊聚类知识分析。
毛坯设计是板料工艺设计中的关键问题,本文在研究翻边成形的应力状态分类的基础上,总结了翻边类型分类组合。根据翻边类型分类组合,提出了组合式翻边毛坯模糊设计方法,分别构建了压缩类翻边毛坯模糊设计系统、伸长类翻边毛坯模糊设计系统、弯曲类翻边毛坯模糊设计系统。为了构建翻边毛坯模糊设计系统,本文提出了基于Table Look-up Scheme板料成形工艺模糊系统构建方法。针对翻边毛坯设计,将翻边零件边界和毛坯边界进行了离散,构建了基于TableLook-up Scheme的翻边毛坯设计系统的输入一输出数据集。然后,研究了TableLook-up Scheme的知识库构建方法,将输入—输出空间进行了模糊划分建立了隶属度函数,根据输入—输出数据集构建了IF—THEN规则,并利用规则强度,解决了规则冲突的问题。然后,选用带有乘积推理机、单值模糊器、中心平均解模糊器,构建了基于Table Look-up Scheme的翻边毛坯模糊设计系统。由于存在隶属度函数获取的主观性、规则冲突及获取等问题,引入了自适应模糊系统。然后,对翻边毛坯自适应模糊设计系统的模糊空间的划分和隶属度函数的形式的影响作了研究,得出了隶属度函数选择高斯函数形式较好,考虑到计算效率和精度,模糊空间划分为3～5份比较合适。以内曲翻边为例,检验了翻边毛坯自适应模糊设计系统的输出。本文最后以S形翻边为例,将其输入翻边毛坯模糊设计系统,从而获得了毛坯形状,并进行了试验验证,成形结果良好。
将免疫克隆算法与近似模型构建方法相结合,提出了基于免疫克隆算法的板料成形工艺优化方法。研究了免疫克隆算法的原理与构建,以VC++为平台编写了克隆算子、变异算子、选择算子,实现了免疫克隆算法。鉴于板料成形问题的复杂性和非线性,导致了其数学模型构建的困难,利用近似模型构建了板料成形工艺多目标优化模型。首先,采用数字模拟的结果构建了响应面空间点,利用二乘法获得了响应面函数,并编写了计算结果接口与响应面函数的求解程序。然后,建立了多目标优化模型,采用免疫克隆算法对其进行优化求解。最后,采用有限元法对最优解进行了精确分析和验证。以内曲翻边为例,建立了起皱和厚度变化的优化目标函数。对免疫克隆算法进行了求解,获得了良好的优化结果。
Sheet metal forming is widely used in automobile, ship-building, aerospace etc. It plays an important part in national economy. The key of sheet metal forming is the forming process planning. Not only is the sheet metal forming process planning scientific, but it is also artistic. The process planning of sheet metal forming contains human creative power and intuitive experience. Traditionally, the forming process planning was designed by engineer according to book knowledge and intuitive experience. And because of that, it led to the restrictions for the application of sheet metal forming process planning systems. The most important causes of uncertainty in the sheet metal forming process planning are lack of information, abundance of information, and ambiguity. Therefore, the effective handling of the uncertainty and nonlinearity constitutes the most urgent problem for the industry and academic world. Bionic intelligence is partly corresponding to the biological information processing system. It has the power of logical reasoning and associative learning for uncertainty and imprecise factors. In the complex system, it can deal with the modeling or optimization problem, which was constituted by the uncertainty factors. Then, in this paper, the bionic intelligence is introduced to solve the uncertainty, imperfection, nonlinearity problems of the sheet metal forming process planning. Not only will the application of improve the intelligent automation of sheet metal forming process planning, but it is also of great significance in theory and in practice.
In this dissertation, the bionic intelligent design theory for sheet metal forming process planning and the key technologies based on the fuzzy theory and immune algorithm of bionic intelligence was studied. The fuzzy synthetic evaluation method was directly introduced to construct the stamped parts forming performance evaluation system, which was used to evaluate the forming performance of the stamped parts. The sheet metal forming process planning system of drawing parts was constituted based on fuzzy theory, and it can simulate the design flow of human being. The calculated algorithm of sheet metal forming technological parameter was proposed. On the basis of fuzzy clustering and statistical theory, the fuzzy clustering knowledge analysis system for springback was built up. The techniques of fuzzy system theory were directly introduced to the blank design of sheet metal forming. And then, the flanging blank fuzzy design system was present. The immune clone algorithm was researched based on immune theory, and the metamodeling was established in the flanging of sheet metal forming, and the process is optimized by the immune clone algorithm.
Due to the vagueness and uncertainty in the sheet metal forming process planning, the fuzzy theory was introduced to this field in this paper, which was a special tool that can simulate the design process of human being.
Evaluating the stamping performance is a key step in sheet metal forming process planning, which is affected by several factors. In order to get the stamping performance, the knowledge of experts should be considered. Fuzzy synthetic evaluation is an effective decision-making method in the comprehensive evaluation of things affected by multiple factors, and can deal with uncertainty problem with domain expert knowledge. Firstly, the influencing factors were selected by the importance of factors. Shape complexity factors, material performance factors, precision factors were selected to establish the first level influencing factor set. Shape complexity factors could be separated into a triple including geometry factor, maximum projection distance factor between two points in XY plane, the ratio factor between height in the Z direction and maximum projection distance between two points in XY plane. The membership functions of the influencing factors were established according to the different effects of each factor. And then, the evaluation set was built based on the evaluation results of the forming performance. The multi-grade Fuzzy synthetic evaluation algorithm for the stamped part was developed. Finally, the forming performance of a typical stamped part was evaluated based on the developed fuzzy synthetic evaluation model, and the perfect result was achieved. According to the result of the evaluation, the membership function and weight set weighed with the evaluation of the stamped parts.
As well known, stamping process design involves lots of empirical knowledge, which prolongs the cycle of design and manufacturing, limits the competitiveness of enterprises. With the development of computer technologies, CAD/CAM/CAE technologies have been widely applied to the design of stamping processes and dies, but it still needs a large number of engineers' experiences. Fuzzy theory was introduced into the process of traditional stamping process design, and a drawing process design system was established, which mainly includes input and output module, knowledge data-base module, process design module. First, according to the object-oriented method, the representation model of stamping knowledge was established. Then, referred to the tool provided by the fuzzy theory converting knowledge data-base to non-linear mapping, the intelligent adjustment model of design process was established. Finally, a typical part was taken as an example to demonstrate the running process of the system, and the result showed that the system is effective.
The traditional sheet metal forming process planning needs a gear mount of parameters. The process parameters can be found in the compendium, which was only built up on simple experiment condition. So, the generalization capacity of process parameters has some limitations, which led to process parameters limitations. For that reason, huge amounts of experiential knowledge should be considered in the sheet metal forming process planning. The algorithm for process parameter modification was developed based on fuzzy theory. One is fuzzy modified coefficient, which was used to multiply with classic process parameters in order to obtain modified process parameters. Another is about modified process parameters, which was calculated from the fuzzy system embedded with classic process parameters and influencing factors. At last, the effectiveness of process parameter modification for drawing rate was validated, and the calculating process was demonstrated.
In the industrial domain of plastic, there is mass of data of experiments and FEA simulation existed in books, test report, engineer experience, and the data is in the state of discrete. In order to discover the implicit and potential pattern or knowledge, the fuzzy clustering method based on statistic theory was introduced to the springback of sheet metal forming. The springback knowledge analysis model for sheet metal forming was studied firstly. And then, the algorithm for fuzzy clustering was researched in order to establish the fuzzy clustering system for spingback of sheet metal forming. After that, the fuzzy clustering model of spingback was obtained after the fuzzy clustering knowledge analysis, and the effectiveness and accuracy of the proposed model and the developed program for springback fuzzy clustering were validated. On the basis of the research of the springback experiments of Mg alloy plate, the fuzzy clustering method was directly introduced to the springback of Mg alloy plate, and the fuzzy clustering knowledge analysis for Mg alloy plate springback was proposed. The membership function and fuzzy clustering model of Mg alloy plate springback were established to get the fuzzy clustering model of Mg alloy plate. The forecasting result of fuzzy clustering model of Mg alloy plate springback is effective and accuracy.
How to design blank shape is the key problem of sheet metal forming. The fundamentals of flanging process were studied deeply, and the new flanging groups were presented. According to the flanging groups, the framework and function of combined blank fuzzy design system of flanging was developed, including straight flanging blank fuzzy design system, stretch flanging blank fuzzy design system and shrink flanging blank fuzzy design system. In order to construct the flanging blank fuzzy design system, the method of Table Look-up Scheme for sheet metal forming process planning was presented. The borders of the flanging part and the blank were separated to construct input-output data set for Table Look-up Scheme method. On the base of the research of Table Look-up Scheme method for knowledge base, the input-output space was separated in order to construct membership function of process variable. The input-output data was used to establish the IF-THEN rules. The problem of rules conflict was solved reliable by rule intensity. After that, the flanging blank fuzzy design system based on Table Look-up Scheme was constructed by product inference engine, singletom fuzzifier and center average defuzzifier. Due to the subjectivity of membership function, rule conflict and rule procurement, the adaptive fuzzy system for flanging blank fuzzy design was described. The influence of separating number of fuzzy space and the shape of membership function was studied. The Gaussian membership function is more suitable for the adaptive fuzzy system for flanging blank fuzzy design than the other types membership function. Fuzzy space would be divided into 3 to 5 parts in the term of computational efficiency and accuracy. The stretch flanging part was taken as an example to demonstrate the running result of the system. With the applications to the reverse flanging part, the effectiveness and accuracy of the blank design capacity of the system was validated by the experiments.
To combine the immune clone algorithm and metamodeling method for sheet metal forming optimization, a method for sheet metal forming optimization based on the immune clone algorithm was developed. The mechanism and framework of the immune clone algorithm were studied, such as clone operator, mutate operator and select operator. The immune clone algorithm was programmed by VC++. Because of the complexity and nonlinear of sheet metal forming, it is difficult to establish the model of sheet metal forming. So, in the dissertation, the metamodeling method was used to construct the multi-objective optimization model of sheet metal forming. Firstly, the design results based on numerical simulations were used to construct response surface functions by least square method in order to establish the multi-objective optimization model of sheet metal forming. Secondly, optimal solutions were gained from the optimization of response surface functions by the immune clone algorithm. Lastly, the optimal solutions from immune clone algorithm were verified by finite element analysis. By taking of the stretch flanging part as an example, the multio-bjective optimization design model consistent with the wrinkle and thickness was constructed. The immune algorithm was used to solve the multi-objective optimization design model and the validity and reliability of optimal solution was verified by numerical analysis of the forming process.
引文
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