知识图谱驱动的工件加工变形知识应用探索  

Exploration of the Application of Knowledge Graph-Driven Knowledge on Workpiece Machining Distortion

作　　者：戚浩 李晓月 孙兆泽 郭悦 陶强 QI Hao;LI Xiaoyue;SUN Zhaoze;GUO Yue;TAO Qiang(College of Mechanical and Electrical Engineering,Qingdao University,Qingdao 266071,China;Qingdao Haier Biomedical Co.,Ltd.,Qingdao 266000,China)

机构地区：[1]青岛大学机电工程学院,山东青岛266071 [2]青岛海尔生物医疗股份有限公司,山东青岛266000

出　　处：《青岛大学学报(工程技术版)》2025年第1期64-71,91,共9页Journal of Qingdao University(Engineering & Technology Edition)

基　　金：国家自然科学基金项目(52305476);山东省自然科学基金项目(ZR2022QE043)。

摘　　要：针对工件加工变形研究领域面临的知识体系碎片化,信息资源孤立分散,检索效率不高,决策支持不足以及缺乏个性化知识推荐服务等问题,利用图算法对构建的工件加工变形知识图谱进行可视化分析,开发了工件加工变形知识推荐系统与智能问答系统。通过对系统的实例验证,结果表明,图算法实现了知识的聚类分析和中心性分析;与传统信息检索系统相比,推荐系统提高了信息检索效率和准确性;问答系统提升了知识响应速度和可解释性。In response to issues in the field of workpiece machining distortion research,such as fragmented knowledge systems,isolated and scattered information resources,low retrieval efficiency,insufficient decision support,and a lack of personalized knowledge recommendation services,a workpiece machining distortion knowledge graph was constructed.Based on this,graph algorithms were applied for visual analysis of the knowledge graph,and a knowledge recommendation system as well as an intelligent question-and-answer system for workpiece machining distortion were developed.The results show that graph algorithms enabled clustering analysis and centrality analysis of knowledge;compared to traditional information retrieval systems,the recommendation system improved retrieval efficiency and accuracy;and the question-and-answer system enhanced knowledge response speed and interpretability.

关 键 词：工件加工变形 知识图谱 知识推荐 知识问答 

分 类 号：TH166[机械工程—机械制造及自动化]