知识-用户行为驱动的飞机工装设计知识推送方法

  • 王佐旭 ,
  • 王鑫 ,
  • 孟爽 ,
  • 郑联语
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  • 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

  网络出版日期: 2024-12-12

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

  • WANG Zuo-Xu ,
  • WANG Xin ,
  • MENG Shuang ,
  • ZHENG Lian-Yu
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Received date: 2024-10-17

  Revised date: 2024-11-29

  Online published: 2024-12-12

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。

本文引用格式

王佐旭 , 王鑫 , 孟爽 , 郑联语 . 知识-用户行为驱动的飞机工装设计知识推送方法[J]. 航空学报, 0 : 1 -0 . DOI: 10.7527/S1000-6893.2024.31417

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.

参考文献

[1]靳江艳黄翔.飞机设计域向工装域映射机理研究[J].航空学报, 2012, 33(12):2330-2337
[2]潘志毅; 黄翔; 李迎光.飞机制造大型工装布局设计方法研究与实现[J].航空学报, 2008, 29(3):757-762
[3]金加奇, 孔祥伟, 赵清洲, 申德华.用于飞机舱门装配的柔性工装设计[J].机械设计与制造, 2023, (3):135-140+145
[4]郭飞燕, 刘检华, 邹方, 翟雨农, 王仲奇, 李少卓.数字孪生驱动的装配工艺设计现状及关键实现技术研究[J].机械工程学报, 2019, 55(17):110-132
[5]庞艳.数字化工装设计管理平台研究与应用[J].智能制造, 2016, (8):22-24
[6]李瑞, 王永鹏, 李昆, 徐伟, 袁娜.基于知识和模块化的工装快速设计研究[J].制造业自动化, 2020, 42(5):95-97
[7]Zhang K, Zhao W, Wang J, Chen L, Guo X.Knowledge push technology based on quality func-tion knowledge deployment[J].Proceedings of the In-stitution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2019, 233(4):1119-1138
[8]聂同攀曾继炎.面向飞机电源系统故障诊断的知识图谱构建技术及应用[J].航空学报, 2022, 43(8):625499-625499
[9]张栋豪, 刘振宇, 郏维强, 刘惠, 谭建荣.知识图谱在智能制造领域的研究现状及其应用前景综述[J].机械工程学报, 2021, 57(5):90-113
[10]于泽源, 赵武, 张凯, 王洋, 于淼.支持产品迭代设计的知识推送方法[J].机械工程学报, 2022, 58(18):292-302
[11]尹昱东, 王保建.半结构装配数据的知识抽取及机床装配知识图谱构建方法研究[J].制造技术与机床, 2022, (11):97-101
[12]李乐乐, 王奕为, 丁超, 陈灏.面向飞机维修与维护的知识图谱应用[J].内燃机与配件, 2019, (23):147-148
[13]余隋怀, 王鹏超, 王磊, 初建杰, 敖卿, 侯幸刚.基于知识工程的产品设计研究综述[J].机械工程学报, 2024, 60(13):216-234
[14] 乔文文.基于知识工程的产品设计技术研究[D]. 华北理工大学, 2022[2024-07-08].
[15]陈洪军, 陈新度, 陈新, 郑德涛.新一代基于知识的工程系统[J].中国机械工程, 2002, (17):58-61
[16]耿忠林, 张祥林.利用知识工程进行自行车车架设计[J].CAD/CAM与制造业信息化, 2006, 7:40-42
[17]密阮建驰, 战洪飞, 余军合.面向企业知识推荐的知识情景建模方法研究[J].情报理论与实践, 2016, 39(4):78-83
[18]徐荣振, 高琦, 王昊, 徐廷.基于序列模式挖掘的变型设计知识推送[J].计算机集成制造系统, 2016, 22(5):1179-1186
[19]Song B, Jiang Z.Proactive search enabled context-sensitive knowledge supply situated in computer-aided engineering[J].Advanced Engineering Informat-ics, 2013, 27(1):66-75
[20]Li M, Wang Z, Yan Z, Liang X, Liu J.Promoting knowledge recommendation in innovative engineering design: a BERT-GAT-based patent representation learning approach[J].Journal of Engineering Design, 2024, 0(0):1-26
[21]Moradi P, Ahmadian S.A reliability-based recommen-dation method to improve trust-aware recommender systems[J].Expert Systems with Applications, 2015, 42(21):7386-7398
[22]王临科, 蒋祖华, 李心雨.面向工程领域的主题多样性知识推荐方法[J].计算机集成制造系统, 2021, 27(1):214-227
[23]叶晨, 战洪飞, 林颖俊, 余军合, 王瑞, 钟武昌.基于推理-情境感知激活模型的设计知识推荐[J].浙江大学学报工学版, 2023, 57(1):32-46
[24]Gao X, Feng Y, Hong Z, Mi S, Tan J.Adaptive de-coupling planning method for the product crowdsourcing design tasks based on knowledge re-use[J].Expert Systems with Applications, 2022, (206):117525-
[25]Liu Z, Lou S, Feng Y, Song X, Tan J.A closed-loop human-computer interactive design method based on sequential human intention prediction and knowledge recommendation[J].Journal of Engineering Design, 2024, 8(35):972-995
[26]梁野, 张树有, 刘晓健, 吴晨睿.基于变权分层激活扩散模型的产品设计知识动态推送技术[J].计算机集成制造系统, 2015, 21(12):3107-3118
[27]Gao Y, Feng Y, Tan J.Exploratory study on cognitive information gain modeling and optimization of per-sonalized recommendations for knowledge reuse[J].Journal of Manufacturing Systems, 2017, (43):400-408
[28]Meng S, Fan W, Wang X, Zheng L, Wang Z.Intelligent design of reconfigurable flexible assembly fixture for aircraft panels based on smart composite jig model and knowledge graph[J]. : .[J].Journal of Engineering De-sign, 2024, :1-35
[29]May R M.Simple mathematical models with very complicated dynamics[J].Nature, 1976, 261(5560):459-467
[30]Wichitaksorn N, Kang Y, Zhang F.Random feature selection using random subspace logistic regression[J].Expert Systems with Applications, 2023, (217):119535.-
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