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一个面向产品变型设计过程的知识处理方法模型 总被引:5,自引:0,他引:5
变型设计是在产品工作原理、基本功能定义不变的情况下,通过对现有产品局部结构型式和尺寸的变异来满足不同工作性能需求的一类设计行为.与创造性设计和适应性设计比较,产品变型设计是一种相对刻板、固定同时应用又十分广泛的设计行为.本文在分析了产品变型设计的基本求解流程之后,提出了一个以基于实例的推理为核心,综合运用规则推理和约束满足方法的知识处理方法模型,并且,结合所开发的"细纱机模块化变型设计系统",从知识表达模式和推理过程两方面对其特点和应用作出了介绍. 相似文献
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针对建立实例库时存在的问题,对基于实例推理的变型设计进行了研究,提出了在PDM环境下建立实例库的方法.分析了实例推理的一般过程,提出了一种基于实例推理的变型设计求解模型,在此基础上, 以汽车产品为例,提出了一种变型设计的检索方法,为实现汽车产品的变型设计奠定了基础. 相似文献
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支持动态变型设计的多领域系统知识建模与推理求解 总被引:1,自引:0,他引:1
基于Modelica语言的多领域系统建模关注物理建模和参数优化等问题,缺乏对产品变型设计的支持.通过扩展多领域基本仿真模型,提出一种结构待定和参数待定的变型产品结构模型.该模型按照参数约束、部件约束和模型约束等知识表达规范融入产品设计知识和经验,采用推理机推理确定产品的结构和参数,实现了基于仿真的动态变型设计.最后以实例验证了动态变型设计方法的实用价值. 相似文献
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基于产品动态模型的智能快速响应设计理论和方法研究 总被引:9,自引:1,他引:8
文中将产品动态模型应用于快速响应变型设计中,研究了快速响应变型设计智能化理论和方法,提出了采用规则推理和实例推理相结合的混合推理策略;并针对设计的过程性,将变型设计分为概念变型设计、装配变型设计和产品定义变型设计;最后分析了基于产品动态模型的智能变型设计过程。 相似文献
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产品变型设计的基本思想是通过改变已有的系列产品或设计实例来适应新的设计需要.本文通过对电机定转子冲压模具结构特征的深入研究,获得产品结构设计知识,开发了电机定转子冲压模具三维参数化CAD系统的原型,实现了面向装配的参数化设计,验证了该方法的可行性. 相似文献
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刘涛 《计算机工程与设计》2008,29(3):771-774
重组企业业务流程可以提高企业对市场的竞争能力.把变型产品的业务流程看作是抽象的变型产品,提出了以实现业务流程重组为目标的变型业务流程设计框架.在该框架中,以场景和刻面概念分别作为描述实例的手段,消除需求和设计间的"语义断层";提出基于树匹配的实例检索算法,以提高实例检索的查准率和查全率. 相似文献
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支持概念及装配建模的智能变型设计系统框架 总被引:12,自引:0,他引:12
概述了目前计算机辅助变型设计中存在的问题,将实例推理技术(CBR)应用于变型设计,提出了一个支持概念建模和装配建模的智能变型设计系统框架,研究了这种智能变型设计的设计过程理论,并对系统的关键技术-实例的表示和了详细的研究。 相似文献
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基于实例推理方法的液压缸智能CAD系统研究 总被引:9,自引:1,他引:9
在机械产品设计阶段,设计者总是借助于已有实例或相似的实例来进行产品开发,针对这一特点,本文以液压缸设计为对象研究基于实例推理的设计方法,提出一种机械产品用实例结构与实例数据相结合的描述方法,论述产品零部件实例的分级描述模型和实例推理方法,实际应用表明,基于实例求解方式是开发系列化产品设计或改进设计智能CAD系统的一种有效的推理方法。 相似文献
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探讨了如何增强CBR对一种常见的时态信息,即时间序列数据的检索能力;分析了已有的基于傅里叶频谱分析的时间序列检索算法应用于CBR时遇到的问题,并根据时态CBR检索的需要,提出了一种新的基于循环卷积和傅里叶变换时间序列检索算法.理论分析和数值实验结果都证明,提出的算法在检索效率上有一定的优势.将采取这种检索方法的时态CBR应用于时间序列的预测问题中,取得了较好的预测效果且具有较高的预测效率. 相似文献
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在应用基于案例推理技术进行智能建模时,案例修改后的案例质量好坏直接影响所建模型的精度,但是由于案例修改对领域知识的依赖性很强,采用一般手工案例修改方法尤法保证案例修改的质量,即无法保证智能推理模型的精度。基于以上原因,该文提出了一种新的案例修改方法,利用KDD技术,通过有效的多值关联规则挖掘算法从运行数据库中挖掘出案例各属性间的依赖关系,得到案例修改的基本关联规则集,在此基础上利用粗糙集理论对基本关联规则集进行简约,然后根据简约后的关联规则进行案例修改。在线对比实验证明,应用本文方法进行案例修改,提商了修改后的案例质量,从而提高了整体智能推理模型的精度。 相似文献
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汽水板式换热过程区间串级智能控制方法 总被引:2,自引:2,他引:0
汽水板式换热过程是以蒸汽阀门开度为输入,以蒸汽流量为内环输出,以供水温度为外环输出的强非线性串级工业过程,受到室外温度和厂区热用户放水的随机干扰,导致供水温度和蒸汽流量大范围波动.本文针对处于干扰环境下的具有不确定性和强非线性串级工业过程,将前馈补偿、串级PI控制和规则推理区间补偿控制相结合,提出了由外环供水温度前馈PI控制、内环蒸汽流量PI控制的串级控制与规则推理的内外环设定值区间补偿控制组成的区间串级智能控制方法,并成功应用于某选矿厂的汽水板式换热过程,工业应用结果表明所提出的方法在室外温度和热用户放水的随机干扰下,可以将供水温度和蒸汽流量同时控制在工艺要求的范围内. 相似文献
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Chi-man Vong Pak-kin Wong Weng-fai Ip 《Engineering Applications of Artificial Intelligence》2011,24(7):1281-1294
Whenever there is any fault in an automotive engine ignition system or changes of an engine condition, an automotive mechanic can conventionally perform an analysis on the ignition pattern of the engine to examine symptoms, based on specific domain knowledge (domain features of an ignition pattern). In this paper, case-based reasoning (CBR) approach is presented to help solve human diagnosis problem using not only the domain features but also the extracted features of signals captured using a computer-linked automotive scope meter. CBR expert system has the advantage that it provides user with multiple possible diagnoses, instead of a single most probable diagnosis provided by traditional network-based classifiers such as multi-layer perceptions (MLP) and support vector machines (SVM). In addition, CBR overcomes the problem of incremental and decremental knowledge update as required by both MLP and SVM. Although CBR is effective, its application for high dimensional domains is inefficient because every instance in a case library must be compared during reasoning. To overcome this inefficiency, a combination of preprocessing methods, such as wavelet packet transforms (WPT), kernel principal component analysis (KPCA) and kernel K-means (KKM) is proposed. Considering the ignition signals captured by a scope meter are very similar, WPT is used for feature extraction so that the ignition signals can be compared with the extracted features. However, there exist many redundant points in the extracted features, which may degrade the diagnosis performance. Therefore, KPCA is employed to perform a dimension reduction. In addition, the number of cases in a case library can be controlled through clustering; KKM is adopted for this purpose. In this paper, several diagnosis methods are also used for comparison including MLP, SVM and CBR. Experimental results showed that CBR using WPT and KKM generated the highest accuracy and fitted better the requirements of the expert system. 相似文献
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In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval.When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily on an extended object oriented/rule based system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers.Our approach to integrating rule based reasoning, case based reasoning and case based retrieval is contrasted to the CABARET and PROLEXS architectures which rely on a centralised blackboard architecture. We discuss in detail how our various cooperating agents interact, and provide examples of the system at work. The IKBALS system uses a specialised induction algorithm to induce rules from cases. These rules are then used as indices during the case based retrieval process.Because we aim to build legal support tools which can be modified to suit various domains rather than single purpose legal expert systems, we focus on principles behind developing legal knowledge based systems. The original domain chosen was theAccident Compensation Act 1989 (Victoria, Australia), which relates to the provision of benefits for employees injured at work. For various reasons, which are indicated in the paper, we changed our domain to that ofCredit Act 1984 (Victoria, Australia). This Act regulates the provision of loans by financial institutions.The rule based part of our system which provides advice on the Credit Act has been commercially developed in conjunction with a legal firm. We indicate how this work has lead to the development of a methodology for constructing rule based legal knowledge based systems. We explain the process of integrating this existing commercial rule based system with the case base reasoning and retrieval architecture. 相似文献
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一种CBR与RBR相结合的快速预案生成系统 总被引:3,自引:0,他引:3
将范例推理(case based reasoning,CBR)与规则推理(rule based reasoning,RBR)两种人工智能技术相结合,实现一种快速预案生成系统.它有效地解决了单纯RBR系统在预案生成过程中的时间延迟缺陷和知识库难以获取的瓶颈.通过CBR工具,能够把以前发生的紧急事件和解决方案生成预案.一旦新的事件发生,首先从预案库中进行案例的相似性检索,如果没有检索到预案或者检索到的预案匹配度很低,再采用RBR系统对紧急事件进行规则推理,然后把推理结果重新存入预案库.实验数据表明,这种方法对单纯RBR系统在时间响应上进行了有效的优化.另外,因为案例的获取比专家系统推理规则的获取容易得多,它同时解决了RBR系统推理规则难以获取的瓶颈.根据这种思想,实现了CBR与RBR结合的快速预案生成系统.目前,它已经应用到抗洪抢险的预案生成和城市应急联动的决策支持上,效果表明它在预案生成速度以及实际可操作性上都具有明显优势. 相似文献