基于知识图谱的煤矿安全风险管控方法

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中图分类号：TD79 文献标志码：A

Abstract：Addressing the challenges of multi-source data fusion and poor real-time early warning capabilities in traditional coal mine safety risk monitoring methods，which result inunsatisfactory performance in real-time risk warning and dynamic response，this paper proposes a coal mine safety risk management method based on knowledge graph.The construction of the coal minesafety risk management knowledge graph included key processs suchas riskknowledge acquisition，dynamic hazard extraction，anddynamic risk management.Risk knowledge acquisition：Potential risks were identified through various standardized methods.A structured ontology model was built using languages such as OWL，and risk point instances and their atributes were entered into theenterprise risk knowledge graph to form asemantic network，laying a foundation for inteligent risk assessment and precise management.Dynamic hazard extraction：Multimodal data collected from different data sources were associated inreal time with risk pointinstances inthe knowledge graph，andthe statusofrisk points wasupdatedaccording topresetalgorithmsandrules.Dynamicrisk management：Foridentified hazards，instant inferencewasrealized through reasoning rules writen in Semantic Web Rule Language （SWRL）.Practical application results showed that thismethodcould accuratelyand rapidlyidentify potential hazardsin the production environment，effectively enhancing risk identificationand early warning capabilities，and providing

systematic support for coal mine safety management.

Key words： coal mine safety risk management; knowledge graph; multi-source data fusion; risk knowledge acquisition; dynamic hazard extraction; dynamic risk management

0引言

煤矿安全领域的数据来源广泛，包括规程文本、设备日志、传感器监测数据、历史事故案例、实时视频监控及专家报告等类型，构成了极为复杂的多源异构数据环境。（剩余12860字）