基于Revit二次开发与深度学习的钢框架节点智能审图OA北大核心CSTPCD

In recent years,in order to improve the work efficiency of drawing review and reduce the rework rate,BIM-based intelligent drawing review and automatic drawing review technologies have become a hot topic in the field of BIM research.However,the joint model,which is crucial in structures,has not yet been studied for automatic compliance check.Against this background,an intelligent drawing review framework based on Revit secondary development and deep learning is proposed,which includes three parts:information extraction,semantic enrichment,as well as compliance reasoning and suggestions.The intelligent drawing review system is developed for four kinds of beam-column joints in steel frame structures.The one-dimensional convolutional neural network trained with joint eigenvalues as samples fully considers the geometric features of the model,and the accuracy of beam-column joint classification reaches 98.59％after optimization,which is higher than that of other commonly used machine learning classification algorithms.The developed compliance reasoning algorithm can complete the construction rule checking and strength checking of the joint model,and put forward optimization suggestions.The developed intelligent drawing review system has completed the intelligent drawing review for a four-story steel frame structure model with a total of 136 beam-column joints.The accuracy rate is 97.79％and the time-consuming is 86 s,which improves the accuracy and efficiency of drawing review compared with manual drawing review.