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  COBie+Interpretable and Complex Spatio-Temporal Relation Reasoning Network-Based Decision Analysis Method for the Tunnel Equipment Maintenance

  With the in-depth research and application of BIM-based tunnel lifecycle management, how to effectively integrate and utilize the multi-source heterogeneous data generated in the management process has been a hot issue of concern. Although relevant researchers have proposed a multi-source heterogeneous data integration method based on IFC standard and ontology in the Architecture, Engineering, and Construction (AEC) area, the IFC standard cannot fully describe the operation and maintenance data and it cannot satisfy the requirements of quick malfunction analysis and maintenance decision analysis for emergency maintenance tasks under the smart management mode. Therefore, this paper proposes a tunnel equipment maintenance decision analysis method based on COBie+interpretable complex Spatio-temporal relation inference network. Based on the COBie standard, this method abstracted the dynamic ontology framework and proposed a new inference model for the whole lifecycle data. It predicts the correspondence between the cause of equipment failure and the current analysis results and uses traceability to update the inference process. This method has been applied in the whole life cycle intelligent management of the Wenyi Tunnel in Hangzhou, which verified the effectiveness and feasibility of the method and provided technical support for the accurate and efficient tunnel equipment maintenance and disposal decision.

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