BIM and ontology-based knowledge management for dam safety monitoring

被引:39
作者
Zhou, Yuhang [1 ,2 ]
Bao, Tengfei [1 ,2 ,3 ]
Shu, Xiaosong [1 ,2 ]
Li, Yueyang [4 ]
Li, Yangtao [1 ,2 ]
机构
[1] Hohai Univ, State Key Lab Hydrol Water Resources & Hydraul Eng, Nanjing 210098, Peoples R China
[2] Hohai Univ, Coll Water Conservancy & Hydropower, Nanjing 210098, Peoples R China
[3] China Three Gorges Univ, Coll Hydraul & Environm Engn, Yichang 443002, Peoples R China
[4] Univ New South Wales, Built Environm, Sydney, NSW 2052, Australia
关键词
Ontology; BIM; Reasoning; Information extraction; Relational database; Dam; Dam safety monitoring system; INDUSTRY; OWL;
D O I
10.1016/j.autcon.2022.104649
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Dam Safety Monitoring Systems (DSMSs) are crucial in evaluating the operational state of dams. However, heterogeneous monitoring data distributed from multiple sources during the dam operation lacks a unified data integration method and prohibits knowledge extraction and intelligent analysis, which currently poses a labor-intensive task. To address this issue, a solution relying on Building Information Modeling (BIM) and domain ontologies is proposed. Specifically, a DSMS domain ontology (OntoDSMS) is developed by comprehensively collecting domain knowledge and extracting context information from the dam information model. Furthermore, a rule-based reasoner and SPARQL queries are implemented. The proposed approach facilitates the effective integration of dam safety monitoring information while reducing retrieval time effectively compared with traditional databases. A case is illustrated to demonstrate the feasibility and practicality of the proposed approach.
引用
收藏
页数:12
相关论文
共 50 条
[41]  
Schreiber A.T., 1995, P 7 DUTCH C ARTIFICI, P159
[42]   Safety Risk Management of Prefabricated Building Construction Based on Ontology Technology in the BIM Environment [J].
Shen, Ye ;
Xu, Min ;
Lin, Yini ;
Cui, Caiyun ;
Shi, Xiaobo ;
Liu, Yong .
BUILDINGS, 2022, 12 (06)
[43]   Unsupervised dam anomaly detection with spatial-temporal variational autoencoder [J].
Shu, Xiaosong ;
Bao, Tengfei ;
Zhou, Yuhang ;
Xu, Ruichen ;
Li, Yangtao ;
Zhang, Kang .
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2023, 22 (01) :39-55
[44]   Dam Safety Evaluation Based on Interval-Valued Intuitionistic Fuzzy Sets and Evidence Theory [J].
Shu, Xiaosong ;
Bao, Tengfei ;
Li, Yangtao ;
Zhang, Kang ;
Wu, Bangbin .
SENSORS, 2020, 20 (09)
[45]   Ontology versus Database [J].
Sir, Michal ;
Bradac, Zdenek ;
Fiedler, Petr .
IFAC PAPERSONLINE, 2015, 48 (04) :220-225
[46]   Modeling multiple space views for schematic building design using space ontologies and layout transformation operations [J].
Suter, Georg .
AUTOMATION IN CONSTRUCTION, 2022, 134
[47]   Ontologies: Principles, methods and applications [J].
Uschold, M ;
Gruninger, M .
KNOWLEDGE ENGINEERING REVIEW, 1996, 11 (02) :93-136
[48]   Development of a BIM-Based Data Management System for Structural Health Monitoring with Application to Modular Buildings: Case Study [J].
Valinejadshoubi, Mojtaba ;
Bagchi, Ashutosh ;
Moselhi, Osama .
JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2019, 33 (03)
[49]   Semantics of model views for information exchanges using the industry foundation class schema [J].
Venugopal, M. ;
Eastman, C. M. ;
Sacks, R. ;
Teizer, J. .
ADVANCED ENGINEERING INFORMATICS, 2012, 26 (02) :411-428
[50]  
Zhang R., 2021, P INT C COMP CIV ENG, P466