| 引用本文: | 葛睿夫,任志刚,林江豪,林越,高祖标.面向注塑产品工艺缺陷的知识图谱构建方法及应用[J].控制理论与应用,2024,41(3):577~585.[点击复制] |
| GE Rui-fu,REN Zhi-gang,LIN Jiang-hao,LIN Yue,GAO Zu-biao.Construction method and application of knowledge graph for process defect of injection molding products[J].Control Theory and Technology,2024,41(3):577~585.[点击复制] |
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| 面向注塑产品工艺缺陷的知识图谱构建方法及应用 |
| Construction method and application of knowledge graph for process defect of injection molding products |
| 摘要点击 2260 全文点击 62 投稿时间：2022-10-31 修订日期：2023-05-18 |
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| DOI编号 10.7641/CTA.2023.20959 |
| 2024,41(3):577-585 |
| 中文关键词 知识图谱 本体模型 知识抽取 专家知识 故障诊断 |
| 英文关键词 knowledge graph ontology model knowledge extraction expert knowledge fault diagnosis |
| 基金项目 广东省重点领域研发计划项目(2021B0101200005), 国家自然科学基金项目(62073088, U1911401)资助. |
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| 中文摘要 |
| 针对现有注塑产品缺陷故障原因排查与定位依靠专家人工诊断效率低、成本高昂等不足, 本文提出了一种
面向注塑产品缺陷的知识图谱构建方法及其应用, 目的在于将专家知识采用知识图谱进行表示, 利用基于知识图谱
的垂直检索技术, 解决故障排查和定位困难的问题. 首先, 文章基于多源异构的故障解决方案文本构建语料库, 并构
建知识本体模型. 其次, 采用面向非结构化文本的知识抽取模型, 将产品缺陷的相关专家知识从原始语料中自动抽
取出来. 最后, 利用Neo4j图数据库实现知识存储及可视化知识图谱的构建. 在所构建的知识图谱中, 探索并实现了
知识智能搜索、故障诊断及工艺卡解析等应用, 展示了知识图谱技术在注塑领域的良好应用前景. |
| 英文摘要 |
| In response to the deficiencies of low efficiency and high costs associated with the existing manual diagnosis
of injection molding product defects, this paper proposes a method for constructing a knowledge graph for injection
molding product defects and its application. The objective is to represent expert knowledge by using a knowledge graph
and utilize knowledge graph-based vertical retrieval techniques to address the difficulties in fault troubleshooting and localization.
Firstly, a corpus of fault resolution solution texts is built based on the multiple heterogeneous sources, and a
knowledge ontology model is constructed. Secondly, a knowledge extraction model for unstructured texts is employed
to automatically extract relevant expert knowledge regarding product defects from the original corpus. Finally, the Neo4j
graph database is used to implement knowledge storage and the construction of a visualized knowledge graph. In the constructed
knowledge graph, applications such as intelligent knowledge search, fault diagnosis, and process card analysis are
explored and implemented, demonstrating the promising application prospects of knowledge graph technology in the field
of injection molding. |
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