Research on BIM-KNN Damage Identification Method for Underground Transportation Hub
In order to achieve the identification and prediction of damage status in underground transportation hub,combined with the research and practice experience of the Optics Valley Complex Hub Project,the BIM-KNN(Building Information Modeling-K-Nearest Neighbors)based damage identification method for underground transportation hub was proposed.Through digital simulation,calculation and analysis of the constructed underground transportation hub scheme,the control index information of feature points was extracted,and the big data training sample set was constructed.Based on the numerical simulation analysis results,feature point monitoring was carried out for weak stress and deformation parts or key parts to obtain the monitoring data information.K measured structural control index monitoring values of feature points were selected as the test sample set.Using limited monitoring point data in test sample set,an improved KNN algorithm was proposed to identify and predict the damage status of underground transportation hubs,and reasonably evaluate the structural health status,assist in operation,maintenance and management decision-making to support structure service life.
underground transportation hubdamage identificationstatistical analysisBIM-KNNbig datasample set
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