重载铁路轨道运维典型病害知识图谱研究

Research on Knowledge Graph of Typical Track Disease in Heavy Haul Railway Track Maintenance and Operation

在复杂服役环境下重载铁路轨道病害频发,但尚未系统建立重载铁路典型病害特征、成因、治理与服役环境的相互关系,导致重载铁路养护维修面临严峻挑战和巨额成本。研究基于重载铁路多年运维数据,构建直观的重载铁路轨道运维典型病害知识图谱,全面系统地展现病害要素之间的相关关系,为重载铁路线路病害的诊断与管理提供了新方法。首先根据重载铁路多年运维数据获取病害特征,分析有关典型病害要素实现本体结构建模;然后,经过实体和实体关系抽取、知识融合和知识存储,考虑重载铁路轨道运维全过程的系统化和整体化,构建反映重载铁路轨道病害与复杂服役环境和运营维修相关关系的综合性知识图谱,为轨道病害的诊断、预防、治理提供辅助决策支持。

In complex operating environments,heavy haul railway tracks frequently experience track disease.However,a systematic understanding of the typical characteristics,causes,management,and their relationship with the operating environment of heavy haul railway track disease has not yet been established.As a result,the maintenance and repair of heavy haul railway tracks face significant challenges and substantial costs.Research utilizes years of operational data to construct an intuitive knowledge graph of typical track disease in heavy-haul railway operations.It comprehensively and systematically presents the interrelationships between various elements of track disease,providing a novel approach for diagnosing and managing line defects in heavy haul railways.Firstly,the characteristics of track disease are obtained from years of operational data,and relevant ontological modeling of typical defect elements is conducted.Then,through entity and entity relationship extraction,knowledge fusion,and knowledge storage,a comprehensive knowledge graph is constructed,considering the systematic and holistic nature of heavy-haul railway track maintenance and operation.This knowledge graph reflects the complex relationships between track defects,the operating environment,and operational maintenance,providing decision support for the diagnosis,prevention,and management of track disease.