基于多源异构数据的风机多模态装配工艺知识图谱建模
收稿日期: 2023-02-22
修回日期: 2023-03-22
录用日期: 2023-04-06
网络出版日期: 2023-04-20
基金资助
国家重点研发计划(2019YFB1706300);上海市科学技术委员会“科技创新行动计划”启明星计划扬帆专项(22YF1400200)
Modeling of Multi-Modal Knowledge Graph for Assembly Process of Wind Turbines with Multi-Source Heterogeneous Data
Received date: 2023-02-22
Revised date: 2023-03-22
Accepted date: 2023-04-06
Online published: 2023-04-20
风力发电机装配工艺信息通常分散于以三维模型、自然文本、图像等多模态信息构成的工艺文件中,导致数据维护和工艺知识获取成本高、效率低.针对这一问题,提出一种基于多源异构数据的风力发电机多模态装配工艺知识图谱建模方法.首先,分析工艺特点给出风力发电机多模态知识工艺图谱(MPKG-WT)中各类概念,完成图谱本体构建;其次,基于多源异构数据及各模态特点,利用数据分析、知识抽取和语义相似度计算等技术实现图谱的自动实例化;最后,以某风力发电机企业装配工艺数据为例,实现MPKG-WT构建,并开发辅助装配工艺设计系统进行验证.研究结果表明,MPKG-WT较单模态图谱蕴含更丰富的知识,且不同模态数据之间能够互补,显著提升装配工艺设计效率.
胡志强, 刘鸣飞, 李琦, 李心雨, 鲍劲松 . 基于多源异构数据的风机多模态装配工艺知识图谱建模[J]. 上海交通大学学报, 2024 , 58(8) : 1249 -1263 . DOI: 10.16183/j.cnki.jsjtu.2023.062
The assembly process information of wind turbines is usually scattered in process documents consisting of multi-modal information, such as 3D models, natural texts, and images. Therefore, the cost of maintaining data and extracting process knowledge is high while the efficiency is low. To solve this problem, a multi-modal knowledge graph-based modeling method for the assembly process knowledge of wind turbines is proposed with multi-source heterogeneous data. First, the concepts in multi-modal process knowledge graph of wind turbine (MPKG-WT) are defined by analyzing the process characteristics of wind turbines to complete the construction of ontology. Then, based on the characteristics of multi-source heterogeneous data and multi-modal information, data analysis, knowledge extraction, and semantic similarity calculation are leveraged to realize the automatic instantiation of the graph. Finally, taking the process data of a wind turbine enterprise as an example, MPKG-WT is constructed and verified by implementing an auxiliary system for process design. The results show that MPKG-WT is more informative than the single-modal graph, and the data in different modals can complement each other, which leads to significant improvements in the efficiency of process design.
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