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KGAssembly: Knowledge graph-driven assembly process generation and evaluation for complex components
International Journal of Computer Integrated Manufacturing ( IF 4.1 ) Pub Date : 2021-03-16 , DOI: 10.1080/0951192x.2021.1891572
Bin Zhou 1 , Jinsong Bao 1 , Zhiyu Chen 1 , Yahui Liu 1
Affiliation  

ABSTRACT

The semantic information of process documents for the assembly of complex components plays an important role in the guidance of assembly operations and the feasibility evaluation of process plans. There are many types of semantic elements contained in assembly process documents. The semantic relationship between assembly elements is complex. Additionally, there is a lack of effective modeling method to deal with the implicit associative semantic knowledge that exists among existing assembly process cases. In this case, it is a great challenge to use the professional knowledge in assembly process documents to guide the intelligent decision-making of assembly process planning and the intelligent analysis of assembly process enforceability evaluation. In this paper, a knowledge graph-driven assembly process generation and evaluation method for complex components is proposed. An APKG (assembly process knowledge graph) model is built. A distributed graph embedding-based model SKGCN (sequence knowledge graph convolutional network) is designed to generate assembly process planning. Furthermore, model and knowledge dual-driven evaluation method for assembly sequences is presented. It provides assembly expert knowledge support for the evaluation method of interference detection of assembly sequence based on point cloud assembly feature recognition. Finally, the approach is evaluated by assembling an aero-engine compressor rotor.



中文翻译:

KGAssembly:知识图驱动的复杂组件装配过程生成和评估

摘要

复杂部件装配工艺文件的语义信息对装配作业的指导和工艺方案的可行性评价具有重要作用。装配工艺文档中包含的语义元素种类繁多。装配元素之间的语义关系是复杂的。此外,缺乏有效的建模方法来处理现有装配过程案例中存在的隐式关联语义知识。在这种情况下,如何利用装配工艺文件中的专业知识来指导装配工艺规划的智能决策和装配工艺可执行性评估的智能分析,是一个很大的挑战。在本文中,提出了一种知识图谱驱动的复杂零部件装配过程生成与评价方法。构建了APKG(装配过程知识图谱)模型。设计了一种基于分布式图嵌入的模型 SKGCN(序列知识图卷积网络)来生成装配过程规划。此外,提出了模型和知识双驱动的装配序列评价方法。为基于点云装配特征识别的装配序列干涉检测评价方法提供装配专家知识支持。最后,通过组装航空发动机压缩机转子对该方法进行了评估。设计了一种基于分布式图嵌入的模型 SKGCN(序列知识图卷积网络)来生成装配过程规划。此外,提出了模型和知识双驱动的装配序列评价方法。为基于点云装配特征识别的装配序列干涉检测评价方法提供装配专家知识支持。最后,通过组装航空发动机压缩机转子对该方法进行了评估。设计了一种基于分布式图嵌入的模型 SKGCN(序列知识图卷积网络)来生成装配过程规划。此外,提出了模型和知识双驱动的装配序列评价方法。为基于点云装配特征识别的装配序列干涉检测评价方法提供装配专家知识支持。最后,通过组装航空发动机压缩机转子对该方法进行了评估。

更新日期:2021-03-16
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