• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2023, Vol. 59 ›› Issue (7): 52-67.doi: 10.3901/JME.2023.07.052

• 绿色产品设计与评价 • 上一篇    下一篇

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面向退役机电产品全生命周期的知识图谱统一建模方法研究

吴秀丽, 马隆洲, 向东, 唐英   

  1. 北京科技大学机械工程学院 北京 100083
  • 收稿日期:2022-06-01 修回日期:2022-07-29 出版日期:2023-04-05 发布日期:2023-06-16
  • 通讯作者: 向东(通信作者),男,1972年出生,博士,教授。主要研究方向为绿色设计与制造,大型构件可靠性。E-mail:20836765@qq.com
  • 作者简介:吴秀丽,女,1977年出生,博士,教授。主要研究方向为制造系统生产调度建模与优化、物流系统建模与优化、智能优化算法。E-mail:wuxiuli@ustb.edu.cn;马隆洲,男,1998年出生,硕士研究生。主要研究方向为知识图谱。E-mail:15901175886@163.com;唐英,女,1968年出生,博士,副教授。主要研究方向为现代机械设计制造与自动化技术,物流工程及标准化技术。E-mail:tangying@ustb.edu.cn
  • 基金资助:
    国家重点研发计划(2020YFB1712902)和国家自然科学基金(52175449, 51975323)

Research on Unified Modeling Method of Knowledge Graph towards the Full Life Cycle of Decommissioned Electromechanical Products

WU Xiuli, MA Longzhou, XIANG Dong, TANG Ying   

  1. School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083
  • Received:2022-06-01 Revised:2022-07-29 Online:2023-04-05 Published:2023-06-16

摘要: 针对退役机电产品逆向物流信息追溯过程中时空分散度高、质量不确定性强、跨组织信息关联度弱等问题,基于知识图谱技术构建了退役机电产品全生命周期统一数据模型。首先提出了从跨组织多源数据到知识图谱构建和应用的全生命周期统一数据建模方法,然后提出了知识图谱构建关键技术,针对知识图谱构建过程中的实体关系联合抽取问题,建立了基于分段注意力融合机制的实体关系联合抽取模型,解决了实体关系重叠问题,并在标准数据集和退役机电产品领域数据集上进行测试,取得了很好的效果,最后建立了退役机电产品全生命周期信息追溯系统。知识图谱的构建实现了退役机电产品生命周期中跨组织信息的统一数据结构,为退役机电产品逆向物流信息追溯提供了强有力的支撑。

关键词: 退役机电产品, 全生命周期信息追溯, 统一数据模型, 知识图谱, 实体关系联合抽取

Abstract: To solve the issues of high spatial and temporal dispersion, strong quality uncertainty and weak inter-organizational information correlation in tracing reverse logistics information of retired mechanical and electrical products, a unified data model based on knowledge graph for the full life cycle information of retired mechanical and electrical products is constructed. Firstly, the architecture to build the unified data model is proposed to deal with the data from different organizations, and then it's key technology is discussed. A joint entity relation extraction model based on segmental attention fusion mechanism is developed to jointly extract the entities and relations task in building the knowledge graph, which can effectively solve the overlapping issue of entities and relationships. The model is tested in the standard datasets and the decommissioned electromechanical products datasets and the results show that the proposed model is effective. Finally, a dynamic information traceability system is developed. The knowledge graph realizes the unified data structure of the cross-organization information of retired electromechanical products in the whole life cycle, and provides a strong support for the reverse logistics information traceability of retired electromechanical products.

Key words: decommissioned mechanical and electrical products, full life cycle information traceability, unified data model, knowledge graph, joint extraction of entities and relations

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