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多视图军事需求模型要素关系冲突检测研究

Research on the Detection Method Dealing with Conflict Based on Multi-view Military Requirement Model Elements
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摘要 由于系统工程设计的专业性,及其表达形式的多样性,致使系统工程设计冲突检测一直成为设计工程的难点。文中以多视图军事需求模型作为系统工程设计表达的标准框架,对其用于系统工程设计描述的视角作为研究对象,对系统工程设计表现形式进行分析,根据目前流行的系统工程设计表达工具特性,进行抽象并归类,总结并建立了四种基本系统工程设计冲突模型,并通过图论方法和矩阵方法进行模型的物理形式和逻辑形式表示,提出针对性的启发式算法和D-S证据推断方法,实现了系统工程设计冲突的自动检测,并结合应用案例,验证方法的有效性和正确性。通过此自动检测方法,不仅可以对需求内容实现无遗漏检查,而且大大提高了冲突检测效率,将完成时间由人工的时、分级缩短至计算机的秒、毫秒级。 Due to the professionalism and the diversity of expressions on system engineering design,it has led to the difficulty on system engineering design collision detection.This paper takes multi-view military requirement model elements as the standard framework for the expression of system engineering design,and takes its perspective of description as the research object,and analyzes the manifestations of system engineering design.According to the characteristics of the popular system engineering design tools,four kinds of conflict models of basic system engineering design are summarized and classified.They are expressed in physical form through graph theory,and logical form through matrix method.Finally,a new method based on heuristic and D-S evidence inference is proposed to detect the conflict of system engineering design automatically,and combined with application cases to verify the effectiveness and correctness of the method.Through this automatic detection method,not only the requirements can be checked without omission,but also improve the efficiency of conflict detection greatly.Even,the time consumption is reduced from hours or minutes level which is determined by human to second or millisecond level which is determined by computer.
作者 冯济舟 吴亮 董世友 FENG Ji-zhou;WU Liang;DONG Shi-you(The 38^(th) Research Institute of CETC,Hefei 230088,China)
出处 《中国电子科学研究院学报》 北大核心 2022年第3期297-304,共8页 Journal of China Academy of Electronics and Information Technology
基金 国防基础科研计划(JCKY2019204A007)。
关键词 系统工程设计 多样性 标准框架 冲突检测 system engineering design diversity standard framework collision detection
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