基于软计算的摩托车智能设计关键技术研究
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摘要
我国是摩托车生产大国,研发摩托车智能设计系统,对于提高摩托车生产率、降低摩托车生产成本、提升我国摩托车的国际竞争力具有重要的实用价值和战略意义。在摩托车的设计过程中,不仅需要大量的领域知识,而且需要很强的求解问题的技巧。将智能设计技术引入到产品设计中,既有利于提高设计自动化与智能化的水平,又有利于提高产品质量、降低成本、缩短产品开发周期。因此本文结合人工智能技术探讨并构建基于知识的摩托车智能设计系统,围绕智能设计的若干关键技术进行分析研究,并将这些技术应用到摩托车的智能化设计中。论文主要采用知识工程技术建立知识库系统,实现基于知识的摩托车参数化建模,为有限元分析提供模型,在结构分析基础上,引入软计算理论与方法中的遗传算法实现摩托车结构参数的全局优化。运用神经网络技术从试验数据中获取隐式知识,实现对知识的联想、推理等高效运用,同时运用粗集理论对经验性知识进行约简,从而找出对决策信息具有重要影响的属性,以及隐含在试验结果中的专家级设计知识。结合以上技术,构建了摩托车智能设计系统,从而为摩托车的方案设计、性能分析提供有效的工具。
论文研究的主要内容如下:
1)根据摩托车现有的研究成果,以及摩托车智能设计系统功能模型,详细分析了智能系统的总体设计思想。在此基础上,提出了摩托车智能设计系统的体系结构,将其分为知识库系统、CAD、CAE及软计算四大模块,从而实现设计方案的选择、参数化建模、方案的仿真验证分析、性能优化及知识获取等。
2)针对摩托车领域知识的多样性、复杂性,提出了集成符号主义与连接主义的知识模型,同时采用了以面向对象为主的混合知识表示方法构建知识库系统及集成多种推理方法的知识应用机制,从而实现对知识的高效运用。
3)针对知识库系统产生的设计方案,为建立基于知识的摩托车自动化设计系统,运用功能结构建模方法,采用基于特征的参数化建模技术,使用面向对象的编程方法,开发基于SolidWorks的摩托车车架参数化设计系统,实现摩托车的自动化设计。
4)在有限元结构分析基础之上,针对其它优化设计需要求导,容易陷入局部寻优的情况,采用了软计算理论与方法中的不依赖于求导的全局寻优的遗传算法,对摩托车整车结构参数实现了全局寻优。
5)为了减少性能试验研究成本,同时有效地获取隐含在试验数据(或数值计算数据)中的隐式知识,引入了软计算理论与方法中的神经网络方法。通过对神经网络反复训练,利用反映输入与输出模式对的内在规律的连接权建立了试验条件与结果的非线性方程。根据基于神经网络的非线性方程,系统可对新的设计条件作出快速的响应。同时将知识表达在网络的连接权与阀值中,实现了对知识联想、推理的高效运用。
6)为了克服神经网络对存储在其连接权与阀值中的知识难以进行描述,对其推理过程难以理解等缺点,提出了采用软计算理论与方法中的粗集理论方法从实验测试结果中识别和提取出潜在的知识,揭示出蕴涵在这些数据背后的内在规律。通过基于粗集理论的属性约简与值约简,在简化决策表的同时,找出对决策信息具有重要影响的属性,获得专家级的领域知识,从而为神经网络的推理过程作出解释,为开发设计人员提供决策支持。
China is one of the major countries of producing motorcycle. The development of intelligent design system for motorcycle is very valuable and significant to enhance productivity, decrease production cost and promote the international competitiveness of China. At the design process of motorcycle, the development of motorcycle needs not only a large number of expertises but also perfect technique of solving problem. To introduce intelligent design technology into the product design is beneficial to enhance the level of design automation and intelligence, and to improve the product quality, reduce production costs, and shorten the development cycle of product. In this dissertation, the knowledge-based intelligent design system of motorcycle is presented, which is integrated with the artificial intelligent technology. Also, several key technologies of intelligent design are analyzed based on the development procedure, and applied into the intelligent design system of motorcycle. Thesis mainly uses the knowledge engineering to set up knowledge base system, and implements knowledge-based parametric modeling of motorcycles, which provide the finite element analysis model. Based on the structural analysis, the introduction of genetic algorithm in the soft computing theories and methods implements global optimization of motorcycle structure parameters. Neural network technology is used to acquire the hidden knowledge from the results to realize the effective reasoning and application of knowledge. And rough set theory is applied to reduce and unitize the experiential knowledge to find out the important attributes affecting the decision-making and extract the expert design knowledge from the simulation and experimental results. According to these studies, the intelligent design system of motorcycle is built up to provide an effective tool for the plan design and performance analysis of motorcycle.
The major contents of the paper are the followings.
1) According to the available study achievements and the design procedure of the intelligent design system of motorcycle, the general design idea of the system is analyzed, and the structure of the system is presented. The system is divided into four modules, knowledge-based systems, CAD, CAE and soft computing, in order to finish the selection of design plan, parametric modeling, the simulation analysis and performance optimization and knowledge acquisition and so on.
2) In accordance with the variety and complexity of the expertise of motorcycle, the knowledge model integrated with the symbol and connection model is presented. And the study emphasis is placed on the oriented-object knowledge representation. Based on the representation method, the knowledge base and its management system, and the application mechanism integrated with several reasoning method are constructed to realize the effective application of the knowledge.
3) Aim to the design plan from Knowledge Base system, in order to set up knowledge-based automated design system for motorcycles, functional structure modeling method, feature-based parametric modeling technology and object-oriented method, are utilized to develop parametric design systems based on SolidWorks for implementation of motorcycle automated design.
4) Based on the finite element structural analysis, since the other methods of optimizing design shall be required to lead, easy to fall into local optimization, the genetic algorithm in soft computing theory is adopted to achieve the global optimization, which is not dependent on method of derivative. Global optimization of motorcycle structural parameters is implemented.
5) In order to reduce the experimental cost and acquire effectively the hidden knowledge from the simulation and experimental results, the neural network technology is introduced into the intelligent system. After the neural network is trained repeatedly, the nonlinear regression equation of the conditions and results of experimental and analysis can be built according to the connecting weights of neural network, which reflect the inner laws of the input and output patterns. Meanwhile, the knowledge is stored in the connecting weights and biases. So, on the basis of the structure of neural network, the intelligent design system of sugarcane harvester can respond to the new design conditions quickly.
6) It is difficult to explain the knowledge stored in the connecting weights and biases of neural network so that rough set theory is utilized to extract the potential knowledge and reveal the inner laws hiding behind the simulation and experimental results. Through the reductions of attributes and values, the important attributes affecting the policy decision can be found out and the expertise can be acquired. Therefore, the reasoning procedure of neural network can be explained and the designer can be provided with policy decision support.
论文研究的主要内容如下:
1)根据摩托车现有的研究成果,以及摩托车智能设计系统功能模型,详细分析了智能系统的总体设计思想。在此基础上,提出了摩托车智能设计系统的体系结构,将其分为知识库系统、CAD、CAE及软计算四大模块,从而实现设计方案的选择、参数化建模、方案的仿真验证分析、性能优化及知识获取等。
2)针对摩托车领域知识的多样性、复杂性,提出了集成符号主义与连接主义的知识模型,同时采用了以面向对象为主的混合知识表示方法构建知识库系统及集成多种推理方法的知识应用机制,从而实现对知识的高效运用。
3)针对知识库系统产生的设计方案,为建立基于知识的摩托车自动化设计系统,运用功能结构建模方法,采用基于特征的参数化建模技术,使用面向对象的编程方法,开发基于SolidWorks的摩托车车架参数化设计系统,实现摩托车的自动化设计。
4)在有限元结构分析基础之上,针对其它优化设计需要求导,容易陷入局部寻优的情况,采用了软计算理论与方法中的不依赖于求导的全局寻优的遗传算法,对摩托车整车结构参数实现了全局寻优。
5)为了减少性能试验研究成本,同时有效地获取隐含在试验数据(或数值计算数据)中的隐式知识,引入了软计算理论与方法中的神经网络方法。通过对神经网络反复训练,利用反映输入与输出模式对的内在规律的连接权建立了试验条件与结果的非线性方程。根据基于神经网络的非线性方程,系统可对新的设计条件作出快速的响应。同时将知识表达在网络的连接权与阀值中,实现了对知识联想、推理的高效运用。
6)为了克服神经网络对存储在其连接权与阀值中的知识难以进行描述,对其推理过程难以理解等缺点,提出了采用软计算理论与方法中的粗集理论方法从实验测试结果中识别和提取出潜在的知识,揭示出蕴涵在这些数据背后的内在规律。通过基于粗集理论的属性约简与值约简,在简化决策表的同时,找出对决策信息具有重要影响的属性,获得专家级的领域知识,从而为神经网络的推理过程作出解释,为开发设计人员提供决策支持。
China is one of the major countries of producing motorcycle. The development of intelligent design system for motorcycle is very valuable and significant to enhance productivity, decrease production cost and promote the international competitiveness of China. At the design process of motorcycle, the development of motorcycle needs not only a large number of expertises but also perfect technique of solving problem. To introduce intelligent design technology into the product design is beneficial to enhance the level of design automation and intelligence, and to improve the product quality, reduce production costs, and shorten the development cycle of product. In this dissertation, the knowledge-based intelligent design system of motorcycle is presented, which is integrated with the artificial intelligent technology. Also, several key technologies of intelligent design are analyzed based on the development procedure, and applied into the intelligent design system of motorcycle. Thesis mainly uses the knowledge engineering to set up knowledge base system, and implements knowledge-based parametric modeling of motorcycles, which provide the finite element analysis model. Based on the structural analysis, the introduction of genetic algorithm in the soft computing theories and methods implements global optimization of motorcycle structure parameters. Neural network technology is used to acquire the hidden knowledge from the results to realize the effective reasoning and application of knowledge. And rough set theory is applied to reduce and unitize the experiential knowledge to find out the important attributes affecting the decision-making and extract the expert design knowledge from the simulation and experimental results. According to these studies, the intelligent design system of motorcycle is built up to provide an effective tool for the plan design and performance analysis of motorcycle.
The major contents of the paper are the followings.
1) According to the available study achievements and the design procedure of the intelligent design system of motorcycle, the general design idea of the system is analyzed, and the structure of the system is presented. The system is divided into four modules, knowledge-based systems, CAD, CAE and soft computing, in order to finish the selection of design plan, parametric modeling, the simulation analysis and performance optimization and knowledge acquisition and so on.
2) In accordance with the variety and complexity of the expertise of motorcycle, the knowledge model integrated with the symbol and connection model is presented. And the study emphasis is placed on the oriented-object knowledge representation. Based on the representation method, the knowledge base and its management system, and the application mechanism integrated with several reasoning method are constructed to realize the effective application of the knowledge.
3) Aim to the design plan from Knowledge Base system, in order to set up knowledge-based automated design system for motorcycles, functional structure modeling method, feature-based parametric modeling technology and object-oriented method, are utilized to develop parametric design systems based on SolidWorks for implementation of motorcycle automated design.
4) Based on the finite element structural analysis, since the other methods of optimizing design shall be required to lead, easy to fall into local optimization, the genetic algorithm in soft computing theory is adopted to achieve the global optimization, which is not dependent on method of derivative. Global optimization of motorcycle structural parameters is implemented.
5) In order to reduce the experimental cost and acquire effectively the hidden knowledge from the simulation and experimental results, the neural network technology is introduced into the intelligent system. After the neural network is trained repeatedly, the nonlinear regression equation of the conditions and results of experimental and analysis can be built according to the connecting weights of neural network, which reflect the inner laws of the input and output patterns. Meanwhile, the knowledge is stored in the connecting weights and biases. So, on the basis of the structure of neural network, the intelligent design system of sugarcane harvester can respond to the new design conditions quickly.
6) It is difficult to explain the knowledge stored in the connecting weights and biases of neural network so that rough set theory is utilized to extract the potential knowledge and reveal the inner laws hiding behind the simulation and experimental results. Through the reductions of attributes and values, the important attributes affecting the policy decision can be found out and the expertise can be acquired. Therefore, the reasoning procedure of neural network can be explained and the designer can be provided with policy decision support.
引文
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