高桩码头结构安全性评价的本体知识协同表征方法
赵经彤 , 王兴洋 , 崔春义 , 季则舟 , 袁立莎 , 侯亮
大连海事大学学报 ›› 2026, Vol. 52 ›› Issue (3) : 105 -115.
高桩码头结构安全性评价的本体知识协同表征方法
An ontology-based holistic knowledge representation method for the safety evaluation of piled wharf structures
针对在役高桩码头结构安全评价过程中可靠指标、分级规则与评价结果难以统一组织与协同表达的问题,本文提出一种基于本体知识库的结构安全性评价知识协同表征方法。该方法以结构整体可靠度分析为定量基础,将工程对象、荷载工况、可靠指标、安全等级和判定规则进行语义化建模,构建高桩码头安全评价本体知识库 OntoP-wSE(Ontology for Piled wharf Safety Evaluation),并利用 SwRL 规则和 SQwRL 查询实现安全等级的自动推理与结果检索。选取某服役 10 年的集装箱高桩码头作为实例进行验证。结果表明:该码头在水平荷载作用下整体可靠指标为 3.2746,对应安全等级 B 级;OntoPwSE 本体知识库能够实现安全评价结果的结构化组织、规则化推理和知识图谱化表达。研究结果可为在役高桩码头结构安全评价知识的协同表征与信息化管理提供方法支撑。
To address the difficulty in uniformly organizing and holistically representing reliability indices, grading rules, and evaluation results in the safety assessment of in-service piled wharf structures, this paper proposed an ontology knowledge base approach for the holistic representation of structural safety evaluation knowledge. Taking the structural global reliability analysis as the quantitative foundation, and semantically modeling engineering objects, load conditions, reliability indices, safety grades, and judgment rules, constructed the Onto-PwSE (Ontology for Piled wharf Safety Evaluation) knowledge base for piled wharf safety assessment, and achieved automatic reasoning for safety levels and result retrieval by using SwRL rules and SQwRL queries. A 10-year-old in-service container piled wharf was selected as an example for verification. The results show that the global reliability index of the wharf under horizontal loads is 3.2746, corresponding to safety grade B. The OntoPwSE ontology knowledge base can realize the structured organization, rule-based reasoning and knowledge-graph-based representation of structural safety evaluation results. The proposed method can provide methodological support for the holistic representation and information-based management of safety evaluation knowledge for in-service piled wharf structures.
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国家重点研发计划(2021YFB2601102)
国家自然科学基金面上项目(52478329)
沈阳市工程结构安全评估与防控重点实验室项目(S230184)
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