航天精密仪器总装设备知识图谱管理范式研究  

Equipment Management Paradigm with Knowledge Graph for Aerospace Instrument General Assembly

作　　者：袁梦琦 孙胜利[1,2,3,4] 金钢 YUAN Mengqi;SUN Shengli;JIN Gang(Shanghai Institute of Technical Physics,Chinese Academy of Sciences,Shanghai 200083,China;Key laboratory of Intelligent Infrared Sensing,Chinese Academy of Sciences,Shanghai 200083,China;University of Chinese Academy of Sciences,Beijing 101408,China;School of Information Science and Technology,ShanghaiTech University,Shanghai 201210,China)

机构地区：[1]中国科学院上海技术物理研究所,上海200083 [2]中国科学院智能红外感知重点实验室,上海200083 [3]中国科学院大学,北京101408 [4]上海科技大学信息科学与技术学院,上海201210

出　　处：《上海航天(中英文)》2025年第2期19-27,共9页Aerospace Shanghai(Chinese&English)

基　　金：国家重点研发计划资助项目(E2K22103N0)。

摘　　要：随着制造系统的发展,系统构成日趋复杂,数据信息的统一管理面临挑战:数据内容缺失、更新缓慢、指称不一致等问题导致信息覆盖、信息偏差。为应对挑战,首先,定义了智能制造背景下的知识图谱(KG)管理范式;其次,提出了针对多源异构数据的自顶而下与自底而上结合构建领域KG的方法,利用自然语言处理(NLP)技术抽取实体,并实现多源异构数据的规范化与标准化;再次,通过实例结合大语言模型展示数据处理、图谱构建与信息查询的结果;最后,探讨了基于KG进一步提升管理智能化的方向。With the development of manufacturing system,the system composition is becoming more and more complex,and thus the unified management of data is facing challenges such as data content missing,slow update,and inconsistent reference,which may lead to the problems of information coverage and information bias.To cope with the challenges,a knowledge graph(KG)management paradigm in the context of intelligent manufacturing is firstly defined.Then,a top-down and bottom-up approach is proposed to construct the domain KG for multi-source heterogeneous data,and the natural language processing(NLP)technology is used to extract entities and achieve the normalization and standardization of the multi-source heterogeneous data.After that,the results of data processing,graph construction,and information query combined with a large language model are demonstrated through examples.Finally,the directions of further improving management intelligence based on KGs are discussed.

关 键 词：设备管理范式 智能实验室 知识图谱(KG) 命名实体识别(NER) 大语言模型 

分 类 号：V19[航空宇航科学与技术—人机与环境工程] TP18[自动化与计算机技术—控制理论与控制工程] TP391.1[自动化与计算机技术—控制科学与工程]