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知识-用户行为驱动的飞机工装设计知识推送方法

王佐旭1,王鑫2,孟爽1,郑联语2   

  1. 1. 北京航空航天大学
    2. 北京航空航天大学机械工程及自动化学院
  • 收稿日期:2024-10-17 修回日期:2024-11-29 出版日期:2024-12-12 发布日期:2024-12-12
  • 通讯作者: 王佐旭
  • 基金资助:
    国家自然科学青年基金;中国先进制造技术发展专项资助项目

Aircraft Assembly Tooling Knowledge Recommendation Approach based on Domain Knowledge Graph and User Behavior Feedback

  • Received:2024-10-17 Revised:2024-11-29 Online:2024-12-12 Published:2024-12-12
  • Contact: Zuoxu WANG

摘要: 随着飞机产品频繁换型,飞机装配工装需进行快速可靠设计,提高工装的研制效率和质量对缩短飞机的生产周期有着极为重要的意义。然而航空制造业的装配工装研制周期长、成本高,设计人员需要消耗大量时间与精力来完成工装的设计工作,并且严重依赖设计人员的个人经验,缺乏有效的工装设计知识支持和传承。为此,本文提出了一种基于知识图谱和用户行为的飞机装配工装设计知识推送方法。该方法首先建立了知识文档库、知识标签网络等知识推送资源,再构建推送情境模型来计算各知识文档的推荐优先度值,并基于用户行为对知识推荐优先度值进行修正,最后将筛选出的知识推送给设计人员。本文基于飞机壁板工装设计为例进行了实例验证,证明了本文所提的基于用户行为的知识推荐参数修正机制的有效性。实例证明,本文方法在推送前5位相关知识文档时,准确率为0.83。某标签搜索次数越多,排序越靠前。相同推荐次数下,用户对知识推荐结果评价“有帮助”,能够有效提高该知识被推荐的优先度。此外,本文基于CATIA平台开发了飞机壁板装配工装设计知识推送软件的原型系统,将该方法应用到飞机壁板装配工装的设计中,帮助工装设计人员更加高效地获取工装相关知识。

关键词: 飞机工装, 工装设计, 知识推送, 知识网络, 知识图谱, 用户行为反馈

Abstract: Facing the challenge of frequent changes on aircraft models, it is necessary to achieve rapid design for aircraft assembly tooling. Aircraft product assembly tooling design is a long-term and high-cost tasks. Designers invest significant time and effort in tooling design, heavily relying on personal experience, with limited support and inheritance of tooling design knowledge. To address this issue, this study proposed an assembly tooling design knowledge recommendation approach based on knowledge graph and user behavior feedback. First, a knowledge document repository and a domain knowledge label network are constructed, forming a knowledge graph. Then by constructing and activating a knowledge push scenario model, the priority of knowledge documents is computed based on their relevance between the knowledge push scenario and knowledge tags. Additionally, a knowledge push ad-justment mechanism is proposed, and the priority of the knowledge documents will be adjusted based on user behaviors. Using air-craft wall panel tooling design as an example, this study validates the effectiveness of the user behavior-based parameter adjustment mechanism in knowledge recommendation. The example demonstrates that the accuracy of the proposed method in pushing the top 5 relevant knowledge documents is 0.83. Results also show that tags with higher search frequency are ranked higher, and user ratings of "helpful" significantly increase the priority of recommended knowledge under the same recommendation frequency. Additionally, a prototype system for aircraft panel assembly tooling design knowledge push is developed on the CATIA platform, applying the method to facilitate designers' efficient access to relevant tooling knowledge.

Key words: Aircraft assembly tooling, tooling design, knowledge recommendation, knowledge network, knowledge graph, user behavior feedback

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