铁道标准设计2026，Vol.70Issue(5)：219-229,11.DOI:10.13238/j.issn.1004-2954.202407180006
列控车载设备故障知识图谱的重叠三元组联合抽取方法
Joint Extraction Method for Overlapping Triples in Fault Knowledge Graph of CTCS On-Board Equipment
摘要
Abstract
[Objective]As the core of the Chinese Train Control System(CTCS),on-board equipment utilizes the knowledge graph to analyze fault cases and realize rapid and accurate identification of fault causes and treatment solutions,which is crucial for railway safety and transportation efficiency.[Methods]To address issues such as error accumulation and poor interactivity caused by traditional pipeline methods in knowledge extraction,a joint extraction method for overlapping triples based on a sequence labeling strategy was proposed.Firstly,based on the defined entity and relationship types,a"position-entity-relationship-role"sequence labeling strategy was employed to achieve the joint labeling of overlapping triples.Secondly,the FMBCR(FaultRoBERTa-MHSA-BiLSTM-CRF incorporating regularization methods)model was constructed to accurately extract the global semantic information from fault texts of CTCS on-board equipment,and its predictive performance was optimized by incorporating a KL(Kullback-Leibler)divergence loss algorithm based on the regularization module READ(REgularization method with adversarial training and dropout).Finally,experimental analysis and knowledge graph visualization construction were conducted,using fault data of CTCS on-board equipment as an example.[Results]Through sufficient comparative experiments and ablation experiments,the results showed that the proposed method realized the joint extraction of overlapping triples under small-sample conditions,and the extraction performance was significantly improved compared with traditional methods.Compared with the widely used CASREL joint extraction model,the FMBCR model improved the precision,recall,and F1 score by 3.0%,4.3%,and 3.7%,respectively.[Conclusion]The research findings provide support for advanced applications such as intelligent information retrieval and decision-making assistance for fault maintenance of CTCS on-board equipment.关键词
列控系统/车载设备故障/知识图谱/联合抽取/重叠三元组/序列标注Key words
Chinese Train Control System/on-board equipment fault/knowledge graph/joint extraction/overlapping triples/sequence labeling分类
交通工程引用本文复制引用
张凝,张振海..列控车载设备故障知识图谱的重叠三元组联合抽取方法[J].铁道标准设计,2026,70(5):219-229,11.基金项目
国家自然科学基金项目(61763025) （61763025）
甘肃省重点研发计划项目(2YF7GA141) （2YF7GA141）
