Method for constructing ontology knowledge graph for HAZOP analysis in chemical processes
化工过程HAZOP分析的本体知识图谱构建方法

摘要

针对化工过程HAZOP分析中知识表达不统一、经验复用困难等问题，提出构建本体知识图谱以实现领域知识的结构化与智能化应用。通过定义核心概念、关系及规则，整合工艺参数、偏差、原因、后果与安全措施等多源信息，建立标准化的HAZOP本体模型。采用语义描述语言与图数据库技术实现知识存储与推理，提升分析过程的系统性与可追溯性。实例验证表明，该方法可有效支持HAZOP分析知识的积累、共享与智能辅助决策，增强风险识别能力。

Abstract

Aiming at the problems of inconsistent knowledge expression and difficult experience reuse in HAZOP analysis of chemical processes, this paper proposes to construct an ontology knowledge graph to realize the structured and intelligent application of domain knowledge. By defining core concepts, relationships, and rules, and integrating multi-source information such as process parameters, deviations, causes, consequences, and safety measures, a standardized HAZOP ontology model is established. Semantic description language and graph database technology are used to realize knowledge storage and reasoning, improving the systematicness and traceability of the analysis process. Case verification shows that this method can effectively support the accumulation, sharing, and intelligent auxiliary decision-making of HAZOP analysis knowledge, and enhance risk identification capabilities.