资源目录
压缩包内文档预览：
编号：6084842
类型：共享资源
大小：784.54KB
格式：RAR
上传时间：2017-11-11
上传人：闰***
认证信息
个人认证
冯**（实名认证）
河南
IP属地：河南
13
积分
- 关 键 词：
-
基于
案例
液压
动力
回路
设计
- 资源描述：
-
基于案例的液压动力回路设计,基于,案例,液压,动力,回路,设计
- 内容简介：
-
【中文 4140 字】基于案例的液压动力回路设计Chi-Man Vong, Pak-Kin Wong, Weng-Fai Ip, and Zhi-Xin Yang科学与技术，澳门大学，澳门cmvong,fstpkw,andyip,zxyangumac.mo摘要：本文介绍了设计和实现自动基于案例的推理（CBR）为一体的液压系统回路设计成功的人工智能典范。在此领域内，对基于推理和液压回路的设计进行了简要回顾。然后提出了自动回路设计和使用 CBR 学习的方法。最后通过应用实例说明了选择 CBR 在学习 工业液压回路的设计的应用价值。关键词：基于案例的推理（CBR） ，适应的案例，液压回路设计。1.介绍计算机在工程设计中的使用已成为行业的一大趋势。今天，不同的商业自动化的计算机辅助设计（CAD）软件可应用在许多工程的自动化设计过程中。然而，CAD 软件在液压系统的设计不像在许多其他工程设计领域一样突出。这主要是由于压力分析的复杂性和在设计过程中缺少最合适的协调方法。在最近的多年来，许多智能 CAD 专家系统的液压回路的研究已在文献中找到。大多数CAD 系统的构建从生产规则 1设计的知识表示或基于和面向对象的集成 2，降低液压子回路的复杂性和技术构件表示。虽然该方法是有效的，收购和维护规则的问题，不仅是软件工程师面临的问题，还有利用该软件的设计师。此外，静态学习的另一个问题是传统的基于规则的系统。为解决传统的继承问题，基于规则的专家系统，人工智能社区提出了另一种推理范式，被称为基于案例的推理（CBR） 。CBR 支持新的学习方式，知识可以附加到知识库中没有广泛的重新编译系统。这是一个 CBR 维护知识的主要优点，花费更少的时间。本文研究了 CBR 在液压系统中的应用设计和一种原型液压回路自动设计系统的开发来验证所提出的方法。_1 当规则被更新，整个系统必须被重新编译。吴越（主编）：ICHCC2011 年，CCIS163 ，第 269-275 页，2011。施普林格出版社 2011 年柏林海德堡2.回顾2.1 基于案例的推理CBR3是一种可以发现类比当前的工作情况和过去的经验（参考案例）的方法。CBR 可以直接利用过去的经验来解决新问题，即确认其相似性与特定的已知问题，来寻找一种解决当前现状的方案。 CBR 已开发出许多系统应用于各种领域 4，5，6，7，8，9，10 ，包括制造，设计，法律，医学，和规划。基本的CBR 构成有以下四条：检索 - 检索匹配以往类似的情况下，针对目前存在的问题；重用 - 利用基于过去的案例的解决方案以解决目前存在的问题 ；REVISE - 修改过去的解决方案，如果出现任何矛盾时，要适用于目前存在的问题；保留 - 随着问题保留最终的解决方案，因为最终的解决方案在将来可能是有用的。当用户输入一个问题时，该问题被解释并转换为一个新的案例推理系统的特定格式。转换后的新情况进入检索的阶段，在新的情况下，再对以前匹配的案例库中推理系统案例。CBR 通常在检索阶段通过一个简单的相似函数来找到最相近的作为当前案例的参考。该公式中列出（1）其中 是 最重要的尺寸，iw和 分别是在输入和检索的情IifRi况下的特征值。对于符号 的特征f值，2.2 液压回路设计液压动力是一种动力传动系统和控制。它可以把液压能转化为机械能，以用于有用的生产工作，如压制或提升。液压系统设计的主要任务是回路设计。一般过程如下：I.回路根据客户所提供的信息，例如：回路最大工作压力，最大负载， 执行器速度，工作周期和应用等。II.根据最大工作压力、最大负载和载荷-位移来决定线性或旋转执行机构的尺寸。III.将计算出的执行器的尺寸 转换为标准尺寸。IV.系统参数，如液压油的流量，压力切换等被确定。V.根据系统参数和设计规格选择适当的执行器子回路 ，泵和泵的子回路。VI.最终选择其他在回路中使用的液压元件。3.CBR 在工业液压回路设计 中的应用在 2.2 节步骤 V，液压工程师们通常习惯于修改现有的 回路，然后设计一个新的回路来为了适应不同情形下的使用。这是因为液压回路的设计通常是相似甚至不同的情况，所以液压工程师必须手动查找通过许多现行有效的电路，然后选择一个类似的和合适的并进行修改。在检索过程的阶段是重复和繁琐的，因为工程师要逐一审查每一个回路。然而，检索现有的回路和使它更好地适应当前的情况，可以强烈支持 CBR。如果现有的回路在计算机数据库中（案例收集库） ，每个回路随着其功能和应用程序特定的存储输出要求，这些参数可以作为案例（回路设计）索引、指标。每当液压工程师想要从案例库检索过去的案例，他只需要输入相应的功能和应用程序的特定要求，和 CBR 的使用（1）计算最相似的案例。如果工程师不满意推荐的案例，那么下一个最相似的案例继续出现。要做到这一点，因为案件相似水平的实例相似度的计算排名不同。在那之后，工程师能够适应或修改手动检索的情况下，由以上过程或应用提供 CBR 适应规则。那些适应规则的具体生产规则来自专家或工程师自己的经验。最后，工程师可以决定此案例是否足够好存储库到案例库，以备将来使用。液压回路的设计不同，不仅是因为回路图的不同，而且与他们的功能属性也有关。为了适应回路，如果某些组件更换，那么属性将也可以通过插入或删除进行修改。 CBR 允许的情况下，这样的结构修饰的属性可以添加或删除。例如，一个工程师检索过去的案例，并执行回路设计的修改，然后数的属性将改变根据，他的子回路通过添加或修改预定义的属性，删除不必要属性的子回路。4.应用实例实现系统能够提供基于回路规格最相似的回路设计。工作环境和前段用户界面回路设计系统如图 1 所示。系统的学习能力这部分中显示出的一个例子与援助。表 1 显示的部分属性在图 2 所显示液压子回路实例的表示。图 1.工作环境和回路设计系统前端用户界面表 1.液压子回路的部分属性绘图名称 变量最大流量 33L/min最大压力 630 巴速度变化的阶段 2压力变化的阶段 1 每当检索到过去类似的案例，就可以重复利用已有的案例。然而，并不是每一个案例都是适应当前系统的，作为任何系统设定的规则，往往是不完整的。在这一刻，用户干预是必要的，以补偿系统的无法适应。用户将会利用自己的专业领域知识来修改案例。为了学习领域知识，由用户执行的操作是通过记录回答问题的步骤。当一个用户要寻找一个合适案例的时候，系统会询问用户执行的操作。一旦用户已经选择了该操作，相应的操作提供给用户选择。在记录操作时，系统可以学习从用户寻找相应的知识。博学的知识被封装称为案例，因为它是用来引导。随后，当出现类似的问题出现时，系统将变得能够拥有通过参照适应个案处理的适应能力。4.1 系统实现学习首先，随着它们各自的属性，现有液压子回路的标准功能块图构建，如上面列出的。在训练阶段的系统，显示出了现有图纸预览列表。用户可以选择一种父子回路，进而推导出一种新的回路。例如，考虑道上述例子，如果用户更改“最大流量 ”属性，从 33L/分钟到 350L/分钟，泵组件的父子 回路必须被替换为新的、一个能够支持流量 350L/分钟。这是借助于生产由用户提供的规则：如果最大流量33L/min，然后用旧的块、其它使用新的块该系统可以保持所有这些生产规则，以适应未来的情况。每当子回路最大流量大于 33L/分钟，它必须选择一个特定的泵组件。由于减压阀组件的变化，一个尺寸较大的泄压阀符号应插在子回路如图 2 所示。附图的变化也可以通过与系统集成基于 AutoCAD 平台。图 2.推荐系统回路设计使用 CBR 的组件的一个例子4.2 设计实例和结果讨论对于一个 110 吨的卧式液压木质输入规格压缩站如表 2 所示。由于回路中没有标准的解决方案设计，所以设计的评价将集中在设计的有效性。 “从原型系统回路设计产生的结果被证实按照规定的规格，由专家从两个演出变化-结构图变化结构 - 速度变异领先的液压工程公司。该回路 的主要贡献是设计系统的设计时间减少。非专家通常花 3、4 天时间完成回路设计。手工设计的主要困难是要找到适当的组件和组件之间的连接。这是因为缺乏通用设计理论，从而发现和理解电路中组件的属性是一个非常费时的任务，即使是专家。 利用 CBR，过去许多回路可重复使用和重新考虑选择的时间满意的电路规格的组件可以被保存。余下的工作主要是回路的设计是如何适应到一个新的适合现有的回路，是比从头开始设计一个全新的回路要简单得多。表 2 中.输入规格的 110 吨卧式液压木制压榨站属性 值执行器组数目 1（柱塞式油缸挤压）最大负载（吨） 100行程长度（毫米） 300最大行程速度（毫米/秒） 30最大挤压速度（毫米/秒） 10安装方法 前部与后部法兰挤压过程中的负荷压力的变化阶段的数目 1控制挤压动作的类型 位置感测执行器的速度阶段 2可接受的噪音等级 60 分贝预计使用寿命 5 年机床操作小时/天 12 小时/天原动机额定转速 1450 转最大系统额定压力 210 巴5.结论CBR 是一个在 AI 的方法，可以极大地支持决策过程人类。 CBR 的最重要的部分是重复使用过去的经验，目前的问题，所以，目前的问题相同的部分可以直接再利用比喻使用的相似，缺失部分的问题是可以解决的专家适应规则。这项工作是一个新的尝试，应用 CBR 方法液压系统电路设计与建设学习能力。该电路设计系统可以极大地减少不必要的时间消耗反复类似的液压回路设计，通过重用过去的案例。此外，计划重新编译由于是不必要的修改电路知识基础学习能力的 CBR。工业液压自动设计系统的原型控制电路已建成使用推荐的方法，它一直验证能够成功。参考文献1.伯顿，RT，萨金特，CM：使用专家系统的设计单，母体乐电路。 ：第二届国际会议流体传动及控制，第 605-610 页（1989 年）2.Chan, K.K：一个面向对象的 ICAD 系统液压回路的实现。理学硕士。论文工程系，英国华威大学（1997 年）3.沃森。 ，玛丽，F. ：基于案例的推理。知识工程 9（4） ，327-354（1994）4.格巴尔，F. ，Vo; ，A.，Grether ，W.，施密特贝尔兹，B.：推理复杂的案件。Kluwer 学术出版社，多德雷赫特（1997）5.Vong, C.M., Wong, P.K.：发动机点火信号的小波包诊断变换和多类最小二乘支持向量机。专家系统应用 38（7） ，8563-8570（2011）6.Vong, C.M., Wong, P.K.:基于案例的适应汽车发动机电子控制单元校准。专家系统的应用 37（4） ，3184-3194（2010）7.Vong, C.M., Wong, P.K., Ip, W.F.:基于案例的分类系统与集群的汽车发动机火花塞点火诊断：IEEE / ACIS9 日的国际会议计算机和信息科学（ICIS ） ，页 17-22。 IEEE 出版社，洛斯阿拉米托斯（2010）8.Vong, C.M., Huang, H., Wong, P.K.:发动机火花点火诊断的小波包变换和基于案例的推理。在 IEEE 国际会议上信息与自动化（ICIA ） ，第 565-570 页。 IEEE 出版社，洛斯阿拉米托斯（2010）9.Vong, C.M., Huang, H., Wong, P.K.:基于案例推理的汽车发动机性能优化。 ：第二届国际计算力学研讨会第 12 届国际会议上加强和促进计算在工程与科学，第 185-190 方法。 AIP 出版社，纽约（2009 年）10.Vong, C.M., Wong, P.K., Huang, H.:基于案例推理的汽车发动机电子控制单元校准。在 IEEE 国际会议信息自动化（ICIA）2009 年，第 1380 至 85 年（2009年）11.Vong, C.M., Leung, T.P., Wong, P.K.:基于案例推理和适应水的生产机械设计。人工工程中的应用智力 15（1） ，567-585（2002） Y. Wu (Ed.): ICHCC 2011, CCIS 163, pp. 269275, 2011. Springer-Verlag Berlin Heidelberg 2011 Case-Based Design for Hydraulic Power Circuit Chi-Man Vong, Pak-Kin Wong, Weng-Fai Ip, and Zhi-Xin Yang Faculty of Science and Technology, University of Macau, Macau cmvong,fstpkw,andyip,zxyangumac.mo Abstract. This paper describes the design and implementation of an automatic hydraulic circuit design system using case-based reasoning (CBR) as one of the successful artificial intelligence paradigms. The domain of case-based reasoning and hydraulic circuit design are briefly reviewed. Then a proposed methodology in automatic circuit design and learning with the use of CBR is described. Finally an application example has been selected to illustrate the usefulness of applying CBR in industrial hydraulic circuit design with learning. Keywords: Case-based reasoning (CBR), adaptation case, hydraulic circuit design. 1 Introduction The use of computers in engineering design has become a major trend in industry. Today, different commercial automatic computer-aided design (CAD) software is available to automate the design process in many engineering applications. However, CAD software in hydraulic system design is not as prominent as in many other areas of engineering design. This is mainly due to the complexity of hydraulic analysis and lack of agreement of the most appropriate approach to the design process. In recent years, many researches on intelligent CAD or expert systems for hydraulic circuits have been found in the literature. Most of the CAD systems are built from production rules 1 for design knowledge representation or integrated rule-based and object-oriented technology 2 for reducing the complexity in hydraulic sub-circuit and component representation. Although the approaches are effective, the acquisition and maintenance of rules are the problems facing by not only the software engineers but also the designers using the software. Moreover, static learning1is another issue of traditional rule-based systems. To resolve the problems inherited from conventional rule-based expert systems, the AI community proposed another reasoning paradigm called case-based reasoning (CBR). CBR supports learning in the way that new knowledge can be appended to the knowledge base without wider recompilation of the system. This is one of main advantages of CBR that maintenance of knowledge takes much less time. This paper studies the application of CBR in hydraulic system design and a prototype automatic hydraulic circuit design system has been developed to verify this proposed methodology. 1Whenever the rules are updated, the whole system has to be recompiled. 270 C. Vong et al. 2 Review 2.1 Case-Based Reasoning CBR 3 is a methodology that allows discovering analogies between a current working situation and past experiences (reference cases). CBR makes direct use of past experiences to solve a new problem by recognizing its similarity with a specific known problem and by applying its solution to find a solution for the current situation. CBR has been used to develop many systems applied in a variety of domains 4, 5, 6, 7, 8, 9, 10, including manufacturing, design, law, medicine, and planning. Basically CBR is constituted with four REs 3: RETRIEVE retrieve similar past case matched against current problem REUSE reuse to solve current problem based on solution of past case REVISE revise the past solution if any contradiction occurs when applied to current problem RETAIN retain the final solution along with the problem as a case if the case is useful in the future When the user inputs a problem, the problem is interpreted and converted as a new case into the specific format of the reasoning system. Then the converted new case enters the stage of RETRIEVAL where the new case is matched against the previous cases in the case library of the reasoning system. In the retrieval stage of CBR usually a simple similarity function is employed to find the nearest neighbor for the current problem from the reference cases. The formula is listed in (1) where wiis the importance of dimension i, fiI and fiRare the values for feature fiin the input and retrieved cases, respectively. For symbolic values of f, 0 if 1 if IRIR iiiiIRiiffffff=. 211()(, ,)nIRii iIRiniiwf fEf f Ww=. (1)2.2 Hydraulic Circuit Design Hydraulic power is one of power transmission systems and control. It converts mechanical energy to hydraulic energy for producing useful work such as pressing or lifting. The main task of hydraulic power system design is circuit design. The general procedure is shown as follows: I. The circuit is designed according to the information provided by the client such as maximum operating pressure, maximum load, speed of actuator, duty cycle and application, etc. II. The sizes of the linear or rotary actuators are determined according to the maximum operating pressure, maximum load and load displacement. III. Convert the calculated actuator sizes into standard sizes. Case-Based Design for Hydraulic Power Circuit 271 IV. The system parameters such as hydraulic oil flow rate, pressure changeover, etc, are determined. V. The suitable actuator sub-circuits, pump and pump sub-circuit is selected based on the system parameters and the design specifications. VI. Other hydraulic components used in the circuit are finally selected. 3 Applying CBR in Industrial Hydraulic Circuit Design In section 2.2 step V, hydraulic engineers are usually accustomed to modify an existing circuit design into a new one for different situation and use. It is because hydraulic circuit design is usually similar even for different situation, so hydraulic engineers have to manually look through many existing effective circuits and then select a similar and suitable one and perform modification. The process is repetitive and tedious in the stage of retrieving, because engineers have to review the circuits one by one. However, the process of the retrieving an existing circuit and adapting it to fit better the current situation can be strongly supported by CBR. If the existing circuits are collected in a computer database (case library), and each circuit is stored along with its functional and application-specific requirements of the outputs, these parameters can serve as the case (circuit design) indexes. Whenever the hydraulic engineer wants to retrieve a past case from the case library, he just needs to input the functional and application-specific requirements, and CBR uses (1) to calculate the most similar past case. If the engineer is not satisfied with the recommended case, then the next most similar past case would be shown. This could be done because the cases are already ranked with different similarity level in the calculation of case similarity. After that, the engineer could adapt or modify the retrieved case manually by the above procedure or by applying the adaptation rules supplied by CBR. Those adaptation rules are specific production rules captured from experts or from the engineers own experience. Finally the engineer can decide if the case is good enough to store into the case library for future use. Hydraulic circuit designs differ by not only the circuit diagram but also the functional attributes along with them. For circuit adaptation, if some components are replaced, then the attributes will also be modified by inserting or deleting some of them. CBR enables structural modification of cases, so that attributes can be added or deleted accordingly. For example, an engineer retrieves an past case and performs modification on the circuit design, then the number of attributes would be changed according to, which sub-circuits are revised by adding predefined attributes or deleting unnecessary attributes in the sub-circuits. 4 Application Example The system implemented is able to recommend most similar circuit design based on the circuit specification. The working environment and front-end user interface of the circuit design system are shown in Fig. 1. The learning ability of the system is illustrated in this part with the aid of an example. Table 1 shows partial attributes of the case representation for a hydraulic sub-circuit shown in Fig. 2. 272 C. Vong et al. Fig. 1. Working environment and front-end user interface of the circuit design system Table 1. Partial attributes of a hydraulic sub-circuit Drawing name Var_1 Max. Flow 33 L/min Max. Pressure 630 Bar Variation steps of speed 2 Variation steps of pressure 1 Whenever a past similar case is retrieved, the case is adapted in order to reuse it for current situation. However, not every case is adaptable by the system, as the adaptation rule set of any system is always incomplete. At this moment, the user intervention is necessary to compensate the inability of adaptation of the system. The users will adapt the case using his domain expertise. In order to learn the domain knowledge from the user, the operation performed by the user is recorded by means of answering questions in step. When a user wants to adapt a case, the system will ask the user which kind of operations to perform. Once the user has chosen the operation, the corresponding actions are supplied to the user to choose. In recording the operations, the system can learn from the user the adaptation knowledge. The learnt knowledge is encapsulated as a case called adaptation case because it is used to guide adaptation. Subsequently, when similar problem case arises, the system will become capable to handle the adaptation by referring to the adaptation case. Case-Based Design for Hydraulic Power Circuit 273 4.1 System Implementation for Learning Initially, the existing standard block drawings of hydraulic sub-circuits have been constructed along with their respective attributes such as the one listed above. In the training stage of the system, a list of preview of existing drawings is shown. The user can select a parent sub-circuit to derive a new circuit. For instance, consider the above example again. If the user changes the attribute “Max. Flow” from 33 L/min to 350 L/min, the pump component of the parent sub-circuit has to be replaced with a new one that is able to support flow rate of 350L/min. This is learnt by means of the production rule supplied by the user: if “Max. Flow” = 33L/min then use old_block else use new_block The system can keep all of these production rules to adapt the future cases. Whenever a sub-circuit has maximum flow rate greater than 33L/min, it has to select a certain pump component. Because of the change of the pressure relief valve component, a larger size pressure-relief valve symbol should be inserted in the sub-circuit as shown in Fig. 2. The change of drawing could also be done by the system integrated with AutoCAD platform. Fig. 2. An example change of components recommended by circuit design system using CBR 4.2 Design Example and Discussion of Results The input specification for an example of a 110-ton horizontal hydraulic wooden squeezing station is shown in Table 2. Owing to no standard solution in the circuit design, so design evaluation will be concentrated on the validity of the design. The results generated from the prototype circuit design system have been verified to perform in accordance with the stipulated specifications by the experts from two Changes of substitution of block drawing Changes of structure Speed variation 274 C. Vong et al. leading hydraulic engineering companies. The major contribution of this circuit design system is the reduction of design lead time. Non-experts normally spend three or four days to finish a circuit design. The major difficulty in manual design is to find appropriate components and connection among components. It is because of the lack of universal design theory, hence finding and understanding the properties of components in a circuit is a very time-consuming task, even for experts. With CBR, many past circuits can be reused and the time for re-considering the selection of components satisfied by the circuit specification can be saved. The remaining effort for a circuit design is how to adapt an existing circuit into a new suitable one and this work is much simpler than designing a brand new circuit from scratch. Table 2. The input specifications of a 110-ton horizontal hydraulic wooden squeezing station Attribute ValueActuator group no. 1 (Ram cylinder for squeezing) Maximum loading (Ton) 100 Stroke length(mm) 300 Max. stroke speed (mm/sec) 30 Max. speed for squeezing (mm/sec) 10 Mounting method Front and rear flange No. of variation stage of the load pressure during squeezing 1 Type of control in squeezing action Position sensing Stage of the actuator speed Two Acceptable noise level 60 db Expected service life time 5 years Machine operating hours/day 12 hours/day Prime mover rated speed 1450 rpm Maximum system operating pressure 210 bar 5 Conclusions CBR is a methodology in AI that can substantially support decision-making process of human beings. The most important part of CBR is to reuse past experience in current problem so that identical parts of the current problem can be directly reused while only similar and missing parts of the problem can be solved by analogy using expert adaptation rules. This work is a new attempt of applying CBR methodology in building a hydraulic circuit design system with learning capability. The circuit design system can dramatically reduce the unnecessary time consumed for repeatedly designing similar hydraulic circuit by reusing past cases. Moreover, program recompilation is unnecessary for modification of circuit knowledge base due to the learning ability of CBR. A prototype automatic design system for industrial hydraulic control circuits has been built using the recommended methodology and it has been verified to work successfully. References 1. Burton, R.T., Sargent, C.M.: The use of expert systems in the design of single and multi-load circuits. In: 2nd International Conference
- 温馨提示:
1: 本站所有资源如无特殊说明，都需要本地电脑安装OFFICE2007和PDF阅读器。图纸软件为CAD,CAXA,PROE,UG,SolidWorks等.压缩文件请下载最新的WinRAR软件解压。
2: 本站的文档不包含任何第三方提供的附件图纸等，如果需要附件，请联系上传者。文件的所有权益归上传用户所有。
3.本站RAR压缩包中若带图纸，网页内容里面会有图纸预览，若没有图纸预览就没有图纸。
4. 未经权益所有人同意不得将文件中的内容挪作商业或盈利用途。
5. 人人文库网仅提供信息存储空间，仅对用户上传内容的表现方式做保护处理，对用户上传分享的文档内容本身不做任何修改或编辑，并不能对任何下载内容负责。
6. 下载文件中如有侵权或不适当内容，请与我们联系，我们立即纠正。
7. 本站不保证下载资源的准确性、安全性和完整性, 同时也不承担用户因使用这些下载资源对自己和他人造成任何形式的伤害或损失。
人人文库网所有资源均是用户自行上传分享，仅供网友学习交流，未经上传用户书面授权，请勿作他用。
川公网安备: 51019002004831号