Safety Monitoring Technology for Building Jacking Construction Based on Digital Twins
This study explores safety monitoring technology for building jacking construction based on digital twins so as to realize effective monitoring and ensure safe and stable progress of construction.A safety monitoring technology architecture for building jacking construction is constructed based on digital twins.Corresponding digital twin virtual models are constructed from four levels(geometry,physics,behavior,and rules)on the basis of the actual construction process of building jacking construction site so as to achieve real-time interaction between the physical model and digital twin virtual model..The data generated by the two are synchronously sent to the cloud to form a digital twin data platform,where the data are classified and processed.Finally,in the machine learning driver module,a safety monitoring model based on convolutional neural networks is constructed.After data denoising and input,model training and other opera-tions,the results of safety monitoring are output and visually presented through the digital twin virtual method.The experimental results demonstrate that this method can achieve safety moni-toring of building jacking construction and show satisfactory results.With fewer epochs,ideal safety monitoring results for jacking construction can be achieved.
digital twinbuildingjacking constructionsafety monitoringdata denoisingconvolutional neural network
NETL
NSTL
万方数据
维普
