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1、外文翻译基于事例推理的夹具设计研究与应用摘要:根据基于事例的设计方法,提出采用工序件的特征信息和夹具的结构特征信息来描述夹具的相似性,并建立了包括这2方面主要特征信息为基础的事例索引码,设计了事例库的结构形式,创建了层次化的事例组织方式;同时,提出了基于知识引导的夹具事例检索算法,以及事例的修改和采用同族事例码进行相似事例的存贮,形成了基于事例推理的夹具设计.所开发的原型系统在型号工程夹具设计等项目的设计过程中得到了应用,并取得了令人满意的使用效果.关键词: 基于事例的推理 夹具设计 CAD夹具是以确定工件安全定位准确为目的的装置，并在加工过程中保持工件与刀具或机床的位置一致不变。因为夹具的结
2、构依赖于产品的特点和在企业规划中加工工序的地位,所以它的设计是制造过程中的瓶颈,制约着效率的提高. 夹具设计是一个复杂的过程,需要有从大量的设计论文中了解质量知识的经验，这些设计论文包括工件的结构设计、涉及加工工艺，和加工环境。当用这些擅长绘制详细设计图的传统的CAD工具（如Unigraphics、CATIA、Pro/E)时,这仍然是一项非常耗时的工作，但是利用以往的设计经验和资源也不能提供一些益处,而这正是提高效率的关键因素. 基于事例推理 (CBR) 的方法适应以往个案解决的办法,建立一个新问题的方法,主要有以下四步骤:检索、利用、修改,并保留.这是一个比用专业系统模仿人类思维有用的使用方
3、法，因为提出一个类似的情况,和采用一些修改,似乎不言自明,而且比人类更直观.所以支持不同事例的设计工具已经在诸多领域中发展起来，如在注射成型及设计、建筑设计、模具设计投死, 规划过程中,还有夹具设计. 孙用六个数字组成代码参数,包括工件的形状、机械部分、轴衬,第一定位装置,第二定位装置和夹紧装置. 但这个系统不能用于除钻床夹具外的其他夹具类型,不能解决储存需要保留的同一参数代码的问题,这在CBR中是非常重要的. 1事例参数和事例图书馆的建立1.1事例参数事例参数应该由工件的所有的特征组成，来区别不同的夹具. 使用他们能够使操作方便. 因为零件的形状是多种多样的, 在生产企业中制造的技术要求也不
4、断发展,许多特征作被用做事例参数将会使搜索速度降低,其主要特征是不重要的,因为分配给每个特征的比重必须减少. 另一方面,事例参数包含所有的特征是困难的。 因此,考虑到实际和快速设计的需求,事例参数要包含工件的主要特征和夹具的结构。事例参数代码由16位数组成：13位数是事例特征 3位数是事例识别数字。 前13位数代表13个特征。 每个数字与特征的一个属性相一致,这可能是*、？、1、2，A、B,，Z，等其中的一个。其中，*是指任何一个,?代表不确定,0代表没有。 系统规定:夹具的类型，工件的形状，位置模式不能是*和?。在设计系统时,三个项目的属性信息没有这些选择,这就意味着必须选择确定的属性。最后
5、三位数是事例识别号码,如果事例特征的13位数是一样的,这三个数字就用来区别他们。该系统还规定:000是用于修正的一个典型事例,其他事例001、002、,这些是用于设计师查找参考事例的. 如果其中一个偶尔需要改变成典型事例,首先它必须要求改成000,前面的自动变成参考事例. 事例索引码的结构如图1所示。 1夹具类型； 6工件重量； 11夹紧模型； 2工件形状； 7工件刚度； 12夹具体； 3工件材料； 8加工内容； 13其他； 4批 量； 9过程所有物； 14到16事例识别码； 5工件比例； 10定位模型； 图1 事例索引码的结构1.2事例库事例库由许多预定义的事例组成。事例的描述是基于事例推理
6、的最重要的问题之一。所以由索引码复合。1.3 事例的层次化夹具的结构相似被认为是整个夹具，成分和内容相似。所以，整个夹具事例库，成分事例库，夹具的成分事例库形成相同。整个夹具的设计资料通常是由工件资料和工件加工资料组成,这就意味着夹具的设计应满足特别功能的需求.全部夹具事例是由功能成分组成，它是用功能成分的名字和数字来进行描述的。成分事例代表成员（成分功能和其他结构成分，主要驱动参数，数字，和它们的约束关系）。成分事例（夹具的最低层）是功能成分和和其他成分的结构。在现代夹具设计中有很多参数化准件和普通非标准件。所以成分事例图书馆应记录特殊参数和保持它们的方法。2事例修改的策略在基于事例的夹具设
7、计中，最重要的是相似点的修改，这样能有助于获得最相似的事例，以及缩短适应时间。根据夹具设计的需求，事例修改的策略使最接近的事例方法和知识指导结合起来。首先在深度上查找，然后在宽度上；知识指导策略意味着在来自客观事物根源的知识规则上查找，这就要首先查找固定类型，然后查找工件的形状，第三查找定位方法。例如，如果事例索引码包括夹具类型的磨削夹具，就只查找所有的磨削夹具，然后查找工件形状的盒子，第三查找一个平面两个销的定位方法。如果没有合适的，就查找深度标点，然后回到最上层，然后再找所有与宽度相关的事例。 修改方法：1） 根据夹具事例库的事例索引信息，查找有关事例库。2） 将事例索引码与事例库的每个事
8、例码匹配，然后计算相似尺寸的价值。3） 整理相似尺寸的次序，最大的架子是最类似的事例。两个事例之间的相似点是基于两个事例特征之间的相似点。相似点尺寸的计算依靠特征的类型。相似点的价值可以通过数字化的价值来计算，例如比较重量分别是50kg 和 20kg的工件。非数字化的价值也能计算，例如，现在前13位索引码都是非数字化的价值。一个夹具的相似尺寸的计算公式如下：其中S表示通用夹具的相似尺寸，n表示索引特性数，表示每个特性的重量，表示事例库中特性和相关夹具的特性的相似尺寸。同时， ，数值计算如下： 其中表示第i个特征的索引特性值，表示事例库中第j个事例的第i个特征的特性值。 所以有两种方法选择相似夹
9、具。一个方法是建立数值。如果通用事例的相似尺寸值比给定的数值小，这些事例就不能选来作相似事例。事例库最初建立的时候，只有一些事例，数值可以建小一点。如果有大量的相似事例，数值就应该建的大一些。另外一个方法是只建立相似事例的数字（例如10），这是类型单里相似尺寸的最大值。3 事例的修改和存储3.1事例的修改 夹具设计中相似事例的修改包括以下三个阶段：1） 成分的替代2） 保持形式不变，调整成分的特性3） 模型重新设计如果夹具的成分是普通的物品，它们能通过使用工具被修改，代替以及删除，这些已经被设计好了。3.2事例的存储 在将一个新的事例保存到事例库之前，设计者必须考虑保存是否有价值。如果这个事例
10、不能增加系统的知识，就没有必要把它保存到事例库里。如果它有价值的话，设计者在保存之前必须分析一下，看看这个事例是否作为标准事例或参考事例被存储了。一个标准事例是一个描述同族事例主要特征的标准。一个同族事例是有事例库中索引码前13位相同而最后三位不同的那些事例组成的。一个标准事例的最后三位通常是“000”。一个参考事例属于同族标准事例，最后三位用不同数字区分。从被解释的概念中，可采用以下方法：1）如果一个新的事例和任何一个存在的事例族一致，和一个存在的标准事例的前13位数相同，那么这个事例就不能存储因为已经这种标准事例了。或者只能作为一个参考事例保存（最后三位不是“000”，而且和其它的不一样）
11、在事例库中。 2）如果一个新的事例和任何一个存在的事例族一致，并且被认为代替这个事例族要比以前的标准事例好，那么这个标准事例就被这个新的事例代替，以前的标准事例作为一个参考事例保存。 3）如果一个新的事例和任何一个存在的事例族不一致，一个新的事例族将会自动产生，并作为标准事例保存到事例库中。4夹具设计中基于事例推理的过程根据夹具设计的特性，夹具设计的基本信息，例如夹具的名字，零件，生产和设计者等等，必须先输入。然后，输入或设计工件的模型。输入有关工件的细节信息，建立事例索引码，然后CBR开始依靠相似尺寸查找相似事例，选出最相似的事例。如果需要的话，事例要满足通用性设计，再存储到事例库中。程序流
12、程图如图2所示 图2 基于事例推理的夹具设计流程图5基于事例推理的夹具设计说明这是一个工件如图3所示。材料是45钢，底座，形状为块状，生产批量为中批等。需要设计成一个用来旋转孔的旋转夹具。图3 需要设计夹具的一个工件（最大尺寸80mmx49mmx22mm）工件的特征值，属性值，事例索引码和重量在表1中列出。 表1 工件的事例索引码和重量 特征名称 特性值 索引码 重量 夹具类型 车床夹具 1 100 工件形状 块状 9 90 工件材料 中碳钢 3 70 批量 中批 2 60 工件比例 小 5 60 工件重量 轻 5 60 工件刚度 硬度强 1 60 加工内容 孔 3 80 程序要求 完成加工
13、3 70 定位方法 三个平面 1 100 夹紧方法 不确定 ？ 90 夹具体 复合 4 80 其他 没有 0 60 通过查找和计算相似点，最相似的事例的事例索引码是19325513321402000，细节信息在表2中列出。 表2 最相似事例的事例索引码特征名称 特性值 索引码夹具类型 车床夹具 1 工件形状 块状 9 工件材料 中碳钢 3 批量 中批 2 工件比例 小 5 工件重量 轻 5 工件刚度 硬度强 1 加工内容 孔 3 程序要求 完成加工 3 定位方法 三个平面 1 夹紧方法 不确定 ？ 夹具体 复合 4 其他 没有 0 相似点的计算如下： 所以夹具的相似尺寸值是0.806，这是在事
14、例库中用于设计的最相似的事例，最相似的事例的结构如图4所示图4 最相似的夹具当成分替代，修改定位模型和夹紧模型，以及调节相关尺寸之后，新的夹具被设计出来，图形如图6所示 图5 需要设计的新夹具因为在事例库中没有相似夹具，新夹具被储存到事例库中。事例索引码是19325523311402000。6 结论 基于事例推理，作为一个问题解决的方法，是一个比模仿人类思想的专业系统更有效的方法，已经在很多难获取知识的领域里得到发展。基于事例推理的优点如下：它和人类的思想很相似；一个事例库通过保存新事例获得自学能力，它比有惯例库更快更容易，它可以更好的传递和解释新的知识，这和惯例库有很大的不同。基于事例推理中
15、提出的一个夹具设计的框架已经被实行了，使用的是支持基础数据的VC+，UG电脑绘图软件。这个框架也已经和普通成分库和典型夹具库结合起来。这个发展的标准系统，用于航空项目，帮助夹具设计者提高设计效率和重新使用先前的设计资源。附录2 英文原文Application and developmentOf case based reasoning in fixture design Abstract: Based on the case based designing (CBD) methodology, the fixture similarity is in two respects: the fun
16、ction and the structure information. Then, the computer aided fixture design system is created on case based reasoning (CBR),in which the attributes of the main features of workpiece and structure of fixture as case index code are designed for the retrieve of the similar cases, and the structure and
17、 hierarchical relation of case library are set up for store. Meanwhile, the algorithm based on the knowledge guided in the retrieve of the similar cases, the strategy of case adapt at ion and case storage in which the case ident if cat ion number is used to distinguish from similar cases are present
18、ed. The application of the system in some projects improves the design efficiency and gets a good result .Keywords: case based reasoning ;fixture design; computer aided design(CAD) Fixtures are devices that serve as the purpose of holding the workpiece securely and accurately, and maintaining a cons
19、istent relationship with respect to the tools while machining. Because the fixture structure depends on the feature of the product and the status of the process planning in the enterprise, its design is the bottleneck during manufacturing, which restrains to improve the efficiency and leadtime. And
20、fixture design is a complicated process, based on experience that needs comprehensive qualitative knowledge about a number of design issues including workpiece configuration, manufacturing processes involved, and machining environment. This is also a very time consuming work when using traditional C
21、AD tools (such as Unigraphics, CATIA or Pro/E), which are good at performing detailed design tasks, but provide few benefits for taking advantage of the previous design experience and resources, which are precisely the key factors in improving the efficiency. The methodology of case based reasoning
22、(CBR) adapts the solution of a previously solved case to build a solution for a new problem with the following four steps: retrieve, reuse, revise, and retain 1. This is a more useful method than the use of an expert system to simulate human thought because proposing a similar case and applying a fe
23、w modifications seems to be self explanatory and more intuitive to humans .So various case based design support tools have been developed for numerous areas2-4, such as in injection molding and design, architectural design, die casting die design, process planning, and also in fixture design. Sun us
24、ed six digitals to compose the index code that included workpiece shape, machine portion, bushing, the 1st locating device, the 2nd locating device and clamping device5. But the system cannot be used for other fixture types except for drill fixtures, and cannot solve the problem of storage of the sa
25、me index code that needs to be retained, which is very important in CBR6.1 Construction of a Case Index and Case Library1.1 Case index The case index should be composed of all features of the workpiece, which are distinguished from different fixtures. Using all of them would make the operation in co
26、nvenient. Because the forms of the parts are diverse, and the technology requirements of manufacture in the enterprise also develop continuously, lots of features used as the case index will make the search rate slow, and the main feature unimportant, for the reason that the relative weight which is
27、 allotted to every feature must diminish. And on the other hand, it is hard to include all the features in the case index.Therefore, considering the practicality and the demand of rapid design, the case index includes both the major feature of the workpiece and the structure of fixture. The case ind
28、ex code is made up of 16 digits: 13 digits for case features and 3 digits for case identification number.The first 13 digits represent 13 features. Each digit is corresponding to an attribute of the feature, which may be one of“*”, “？”, “1”, “2”,“A”,“B”, “Z”, etc. In which, “*” means anyone, “?” unc
29、ertain, “0” nothing.The system rules: fixture type, workpiece shape, locating model cannot be “*”or“?”. When the system is designed, the attribute information of the three items does not have these options, which means the certain attribute must be selected. The last three digits are the case identi
30、fication number, which means the 13 digits of the case feature are the same, and the number of these three digits is used for distinguishing them.The system also rules: “000” is a prototype case, which is used for retrieval, and other cases are “001”,“002”, which are used for reference cases to be s
31、earched by designers. If occasionally one of them needs to be changed as the prototype case, first it must be required to apply to change the one to “000”, and the former is changed to referential case automatically.The construction of the case index code is shown in Fig.1.1.2 Case libraryThe case l
32、ibrary consists of lots of predefined cases. Case representation is one of the most important issues in case based reasoning. So compounding with the index code,.1.3 Hierarchical form of CaseThe structure similarity of the fixture is represented as the whole fixture similarity, components similarity
33、 and component similarity. So the whole fixture case library, components case library, component case library of fixture are formed correspondingly. Usually design information of the whole fixture is composed of workpiece information and workpiece procedure information, which represent the fixture s
34、atisfying the specifically designing function demand. The whole fixture case is made up of function components, which are described by the function components names and numbers. The components case represents the members. (function component and other structure components， main driven parameter, the
35、 number, and their constrain relations.) The component case (the lowest layer of the fixture) is the structure of function component and other components. In the modern fixture design there are lots of parametric standard parts and common non standard parts. So the component case library should reco
36、rd the specification parameter and the way in which it keeps them. 2 Strategy of Case RetrievalIn the case based design of fixtures ,the most important thing is the retrieval of the similarity, which can help to obtain the most similar case, and to cut down the time of adaptation. According to the r
37、equirement of fixture design, the strategy of case retrieval combines the way of the nearest neighbor and knowledge guided. That is, first search on depth, then on breadth; the knowledge guided strategy means to search on the knowledge rule from root to the object, which is firstly searched by the f
38、ixture type, then by the shape of the workpiece, thirdly by the locating method. For example, if the case index code includes the milling fixture of fixture type, the search is just for all milling fixtures, then for box of workpiece shape, the third for 1plane+ 2pine of locating method. If there is
39、 no match of it, then the search stops on depth, and returns to the upper layer, and retrieves all the relative cases on breadth.Retrieval algorithms:1)According to the case index information of fixture case library, search the relevant case library;2)Match the case index code with the code of each
40、case of the case library, and calculate the value of the similarity measure;3)Sort the order of similarity measure, the biggest value, which is the most analogical case.Similarity between two cases is based on the similarity between the two cases. features. The calculation of similarity measure depe
41、nds on the type of the feature. The value of similarity can be calculated for numerical values, for example, compareWorkpiece with the weight of 50kg and 20kg. The value can also be calculated between non numerical values, for example, now the first 13 digits index code is all non numerical values.
42、The similarity measure of a fixture is calculated as follows: where S is the similarity measure of current fixture, n is the number of the index feature, is the weight of each feature, is the similarity measure of the attribute of the i2th feature with the attributeof relative feature of the j-th ca
43、se in the case library. At the same time, , the value counts as follows:.Where is the value of the index attribute of the i-th feature, and is the value of attribute of the relative i-th feature of the j-th case in case library.So there are two methods to select the analogical fixture. One is to set
44、 the value. If the values of similarity measure of current cases were less than a given value, those cases would not be selected as analogical cases. When the case library is initially set up, and there are only a few cases, the value can be set smaller. If there are lots of analogical cases, the value should get larger. The other is just to set the number of the analogical cases (such as10), which is the largest value of similarity measure from the sorted order.3 Case adaptation and Case Storage3.1 Case adaptation The modification of the analogical case in the fix
