面向工业数字孪生的三层知识图谱结构设计方法
Three Layer Knowledge Graph Architecture for Industrial Digital Twins
唐昕 1孙宇菲 1王钰珏 1石敏 2朱登明3
作者信息
- 1. 中国科学院计算技术研究所 北京 100190;华北电力大学控制与计算机工程学院 北京 102206
- 2. 中国科学院计算技术研究所 北京 100190
- 3. 华北电力大学控制与计算机工程学院 北京 102206
- 折叠
摘要
随着工业领域数字化和智能化的发展,企业正面临着提高生产效率、降低生产成本、优化生产过程以及实现实时监控等挑战.数字孪生技术作为一种有效的解决方案,受到了广泛关注.然而,工业建设数字孪生过程中存在数据获取与整合、模型构建与更新以及实时性与精度等难点.为解决这些问题,提出了一种基于数字孪生的知识图谱概念-实例-模块结构设计方法.数字孪生知识图谱模型采用概念-实例-模块三层架构,概念层通过知识图谱建立全面有机的知识网络;实例层进行数字化建模,实现理论参数的真实再现;知识模块层则将前两层知识进行融合,形成功能模块,以实现全面监测和控制.这一模型能够对工业加工知识进行更为准确、细致的建模和分析,帮助企业实现数字化建模、精确仿真模拟、预测分析、异常检测等高级应用功能.
Abstract
As digitalization and intelligence continue to develop in the industrial field,enterprises are facing challenges in impro-ving production efficiency,reducing production costs,optimizing production processes,and achieving real-time monitoring.Digital twin technology has received widespread attention as an effective solution.However,there are difficulties in data acquisition and integration,model construction and updating,and real-time performance and accuracy in the process of industrial digital twin con-struction.To address these issues,this paper proposes a concept-instance-module structure design method based on digital twin knowledge graph.The digital twin knowledge graph model proposed in this paper adopts a three-layer architecture of concept-in-stance-module.The concept layer establishes a comprehensive and organic knowledge network through the knowledge graph.The instance layer achieves digital modeling to reproduce theoretical parameters realistically.The knowledge module layer integrates the knowledge of the previous two layers to form functional modules for comprehensive monitoring and control.This model can provide more accurate and detailed modeling and analysis of industrial processing knowledge,helping enterprises to achieve ad-vanced application functions such as digital modeling,accurate simulation,predictive analysis,and anomaly detection.
关键词
数字孪生/知识图谱/智能制造/生产优化/质量控制Key words
Digital twin/Knowledge graph/Intelligent manufacturing/Optimization of the production process/Quality control引用本文复制引用
基金项目
国家重点研发计划(2020YFB1710400)
出版年
2024
NETL
NSTL
万方数据