支持产品智能化设计的知识服务方法研究

doi:10.3969/j.issn.1000-1093.2016.11.019

摘要/Abstract

摘要： 为实现产品智能设计中计算性问题和推理决策性问题的求解以及二者的有效结合，提出一种支持产品智能化设计的知识服务方法，即包括知识服务策略的制定和知识环境的构建两个方面。该方法通过分析设计知识自身特点以及与设计过程之间的关系，将设计知识分为业务领域、经验规则、实例方案和算法模型4种类型，并针对不同类型知识制定相应的服务策略；基于知识模板和组件模板对不同类型的知识进行形式化描述，并给出基于本体的设计知识语义建模流程；通过方案评价、方案修改将设计知识融入到基于实例推理活动中，实现知识的辅助决策；对设计工具进行集成和过程封装，实现了自动化计算。设计开发了基于知识的智能设计系统，并以枪管为对象进行了实例验证，证明了所提方法的有效性。

关键词: 人工智能, 知识服务, 知识重用, 推理决策, 枪管设计

Abstract: To solve the problems of computation and reasoning decision in the product intellectualized design and achieve a combination of both, a knowledge service method for supporting product intellectualized design is proposed, which includes the development of knowledge service strategy and the construction of knowledge environment. The design knowledge is divided into four types, i.e. business domain, empirical rule, instance scenario and iteration calculation, by analyzing the features of design knowledge and the relationship between it and design process. A appropriate service strategy is developed for the different types of knowledge, and the formal descriptions of them are given based on knowledge and component templates. An ontology-based semantic modeling process of design knowledge is presented. On this basis, through evaluation and modification of scheme, the design knowledge is integrated into the instance-based reasoning activities, and the automated computation is achieved by tools integration and procedure packaging. A knowledge-based intelligent design system is developed. The proposed method is demonstrated by taking a gun barrel for example. The result shows that the method is effective.

Key words: artificial intelligence, knowledge service, knowledge reuse, reasoning decision, barrel design

中图分类号:

TP182

王儒，王国新，阎艳，郝佳，石学海，明振军. 支持产品智能化设计的知识服务方法研究[J]. 兵工学报, 2016, 37(11): 2101-2113.

WANG Ru, WANG Guo-xin, YAN Yan, HAO Jia, SHI Xue-hai, MING Zhen-jun. Knowledge Service Method for Supporting Product Intellectualized Design[J]. Acta Armamentarii, 2016, 37(11): 2101-2113.

参考文献

［1］ Gianfranco L R. Knowledge based engineering: between AI and CAD. Review of a language based technology to support engineering design［J］. Advanced Engineering Informatics, 2012, 26(2): 159-179.
［2］肖人彬, 周济, 查建中. 智能设计: 概念、发展与实践［J］. 中国机械工程, 1997, 8(2): 74-76.
XIAO Ren-bin, ZHOU Ji, CHA Jian-zhong. Intelligent design: concept, development and practice［J］. China Mechanical Engineering, 1997, 8(2): 74-76. (in Chinese)
［3］ Richard C, Wim J C V, Michel J L, et al. A multi-disciplinary implementation methodology for knowledge based engineering: KNOMAD［J］. Expert Systems with Applications, 2010, 37(11): 7336-7350.
［4］ Zbigniew K, Maria M, Stefan Z, et al. CBR methodology application in an expert system for aided design ship's engine room automation［J］. Expert Systems with Applications, 2005, 29(2): 256-263.
［5］何勇. 火炮装药设计专家系统的设计与实现［J］. 兵工学报, 2000, 21(2): 171-173.
HE Yong. Design and implementation of an expert system of gun charge design［J］. Acta Armamentarii, 2000, 21(2): 171-173. (in Chinese)
［6］吴晓云, 马大为, 李四超. 基于粗糙层次分析法的武器系统方案智能决策技术［J］. 兵工学报, 2005, 26(6): 803-806.
WU Xiao-yun, MA Da-wei, LI Si-chao. Intelligent decision technology for weapon system scheme based on rough analytical hierarchy process［J］. Acta Armamentarii, 2005, 26(6): 803-806. (in Chinese)
［7］ Burton R T, Sargent C M, Schoenau G J, et al. The use of multiple independent gains for a repetitive low frequency duty cycle in a hydraulic system［C］∥The JFPS International Symposium on Fluid Power. Tokyo, Japan: The Japan Fluid Power System Society, 1993.
［8］ Kolodner J L. An introduction to case-based reasoning［J］. Artificial Intelligence Review, 1992, 6(1): 3-34.
［9］陈靖芯, 李红, 徐晶, 等. 基于知识的智能化设计方法及其实现［J］. 农业机械学报, 2003, 34(4): 109-112.
CHEN Jing-xin, LI Hong, XU Jing, et al. Knowledge-based intelligent design and its application［J］. Transactions of the Chinese Society for Agricultural, 2003, 34(4): 109-112. (in Chinese)
［10］石峰, 娄臻亮, 张永清, 等. 注塑模浇注系统智能设计的一种混合知识模型［J］. 上海交通大学学报, 2003, 37(5): 754-757.
SHI Feng, LOU Zhen-liang, ZHANG Yong-qing, et al. A hybrid knowledge model for intelligent design of injection molding feed system［J］. Journal of Shanghai Jiao Tong University, 2003, 37(5): 754-757. (in Chinese)
［11］ Peng G, Chen G, Wu C, et al. Applying RBR and CBR to develop a VR based integrated system for machining fixture design［J］. Expert Systems with Applications, 2011, 38(1): 26-38.
［12］ Yu Y X, Liao H K, Zhou Y, et al. Reasoning and fuzzy comprehensive assessment methods based CAD system for boiler intelligent design［J］. Journal of Mechanical Science & Technology, 2015, 29(3): 1123-1130.
［13］赵辉, 席平. 基于知识集成模型的产品快速设计［J］. 北京航空航天大学学报, 2006, 33(1): 123-126.
ZHAO Hui, XI Ping. Product rapid design based on integrated knowledge model［J］. Journal of Beijing University of Aeronautics & Astronautics, 2006, 33(1): 123-126. (in Chinese)
［14］ Guo Y G, Hu J, Peng Y H. A CBR system for injection mould design based on ontology: a case study［J］. Computer-Aided Design, 2012, 44(6): 496-508.
［15］余旭, 刘继红, 何苗. 基于领域本体的复杂产品设计知识检索技术［J］. 计算机集成制造系统, 2011, 17(2): 225-231.
YU Xu, LIU Ji-hong, HE Miao. Design knowledge retrieval technology based on domain ontology for complex products［J］. Computer Integrated Manufacturing Systems, 2011, 17(2): 225-231. (in Chinese)
［16］王国新, 阎艳, 张祥, 等. 面向坦克装甲车辆创新与快速设计的知识建模方法研究［J］. 兵工学报, 2009, 30(增刊1): 100-105.
WANG Guo-xin, YAN Yan, ZHANG Xiang, et al. A knowledge modeling approach of innovation and rapid design for armored vehicle［J］. Acta Armamentarii, 2009, 30(S1): 100-105. (in Chinese)
［17］明振军, 阎艳, 王国新. 基于可配置模板的产品设计知识多维度表达方法［J］. 北京理工大学学报, 2014, 34(9): 917-922.
MING Zhen-jun, YAN Yan, WANG Guo-xin. Multi-dimensional representation for product design knowledge based on configurable knowledge template［J］. Transactions of Beijing Institute of Technology, 2014, 34(9): 917-922. (in Chinese)
［18］郝佳, 杨海成, 阎艳, 等. 面向产品设计任务的可配置知识组件技术［J］. 计算机集成制造系统, 2012, 18(4): 705-712.
HAO Jia, YANG Hai-cheng, YAN Yan, et al. Configurable knowledge component technology oriented to product design tasks［J］. Computer Integrated Manufacturing Systems, 2012, 18(4): 705-712. (in Chinese)
［19］ Ke C B, Huang Z Q. Self-adaptive semantic web service matching method［J］. Knowledge-Based Systems, 2012, 35: 41-48.
［20］刘长毅, 徐诚, 刘震. 基于知识的枪管CAD系统的研究与开发［J］. 机械科学与技术. 2000, 19(1): 161-163.
LIU Chang-yi, XU Cheng, LIU Zhen. Research and development of barrel CAD system based on acknowledge［J］. Mechanical Science and Technology. 2000, 19(1): 161-163. (in Chinese)

[1]	赵书彬，徐诚. 基于功能分解结构模型的工程知识自动提取与组织方法[J]. 兵工学报, 2020, 41(10): 1950-1961.
[2]	刘昊，张策，丁文韬. 基于智能对抗进化的联合火力打击任务规划方法[J]. 兵工学报, 2019, 40(6): 1287-1296.
[3]	栗大鹏, 梁伟. 针对非合作目标的自适应网格聚类算法[J]. 兵工学报, 2017, 38(11): 2166-2175.
[4]	焦玉民1,2, 王强1, 徐婷1, 谢庆华2, 王海涛1. 基于GA-Q-learning 算法的虚拟维修作业规划模型[J]. 兵工学报, 2013, 34(5): 627-633.
[5]	董文1，方向1，范磊1，杨力1，雷志刚. 基于斯坦纳树的雷场网络大面积损坏修复策略[J]. 兵工学报, 2013, 34(2): 197-202.
[6]	陈方涵，张肃，王文生. Curvelet变换在低对比度目标识别中的应用[J]. 兵工学报, 2012, 33(6): 688-694.
[7]	徐超，王长龙，孙世宇，陈鹏，绳慧. 双小波神经网络迭代的漏磁缺陷轮廓重构技术[J]. 兵工学报, 2012, 33(6): 730-735.
[8]	杨博，王向华，邵利平，覃征，于维虎. 基于群集智能的传感器管理方法研究[J]. 兵工学报, 2012, 33(2): 155-162.
[9]	宋小杉，蒋晓瑜，罗建华，姚军. 基于类间距的径向基函数-支持向量机核参数评价方法分析[J]. 兵工学报, 2012, 33(2): 203-208.
[10]	康一梅，谢晚冬，胡江，黄琪. 目标尺度自适应的Mean Shift跟踪算法[J]. 兵工学报, 2011, 32(2): 210-216.
[11]	王红霞，潘红兵，叶晓慧. 多故障的测试序列问题研究[J]. 兵工学报, 2011, 32(12): 1518-1523.
[12]	彭颖，沈怀荣，马永一. 一种新的冲突证据融合方法[J]. 兵工学报, 2011, 32(1): 78-84.
[13]	于海全, 彭高亮, 刘文剑. 基于虚拟环境的维修性信息模型的建立[J]. 兵工学报, 2010, 31(7): 998-1002.
[14]	杨日杰₁，吴芳₁，徐俊艳₁，高青伟₂. 基于马尔可夫过程的水下运动目标启发式搜索[J]. 兵工学报, 2010, 31(5): 586-591.
[15]	童仲志₁，张媛₁，邢宗义₁，秦勇₂，贾利民₂. 某装备扫雷犁系统的遗传神经网络建模研究[J]. 兵工学报, 2010, 31(5): 650-656.