面向矿井提升机的故障知识图谱构建与应用  

Construction and Application of Fault Knowledge Graph for Mine Hoist

作　　者：董晓辉 郭庭甫 朱海江[2] 党小超 李芬芳 DONG Xiaohui;GUO Tingfu;ZHU Haijiang;DANG Xiaochao;LI Fenfang(College of Computer Science&Engineering,Northwest Normal University,Lanzhou 730070,China;Jinchuan Group Co.,Ltd.Longshou Mine,Jinchang,Gansu 737100,China)

机构地区：[1]西北师范大学计算机科学与工程学院,兰州730070 [2]金川集团股份有限公司龙首矿,甘肃金昌737100

出　　处：《计算机工程与应用》2024年第14期348-356,共9页Computer Engineering and Applications

基　　金：国家自然科学基金(62162056);甘肃省高等学校产业支撑计划项目(2021CYZC-06)。

摘　　要：针对矿井提升机故障领域公开数据较少、故障知识难以被有效利用的问题,提出了一种矿井提升机故障知识图谱构建方法。该方法引入故障文本分类流程处理目标语料存在的信息冗余问题;利用词典嵌入BERT和BiLSTM-CRF结合进行实体识别,通过ERNIE进行实体关系抽取,并将抽取到的三元组存储在Neo4j图数据库中,在此基础上,实现了一个基于矿井提升机故障知识图谱的智能问答系统。该知识图谱能够较好地揭示矿井提升机故障间的复杂关联关系,实现相关故障的根因分析,为矿井提升机故障诊断提供支撑。In view of the problem that the public data in the field of mine hoist fault is less and the fault knowledge is difficult to be effectively utilized,this paper proposes a method for constructing a mine hoist fault knowledge graph.This method firstly introduces a fault text classification process to deal with the information redundancy problem existing in the target corpus.Then it uses dictionary embedding BERT and BiLSTM-CRF combination for entity recognition,uses ERNIE for entity relation extraction,and stores the extracted triples in Neo4j graph database.On this basis,an intelligent question answering system based on mine hoist fault knowledge graph is realized.This knowledge graph can reveal the complex correlation between mine hoist faults,realize the root cause analysis of related faults,and provide support for mine hoist fault diagnosis.

关 键 词：矿井提升机 故障知识图谱 文本分类 实体识别 关系抽取 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]