Research On The Automatic Detection And Simulation Of Structural Components Of Building Engineering

With the advancement of the urbanization process and the expansion of the construction scale,many engineering projects need to be started at the same time,and then the problems of engineering management,such as lack of manpower,ineffective supervision,and delay of schedule,are highlighted in the project management.Therefore,strengthening the intelligent management of the project also highlights its importance.Furthermore,in recent years,many cities in China have issued notices to promote the use of remote video surveillance systems at construction sites.The extensive use of the construction site monitoring system has provided massive image/video data for project management.These image/video data contain abundant construction information on the construction site that can be used by project managers to analyze construction activities.With the development of emerging technologies such as computer vision technology and deep learning,the application of emerging technologies to improve the level of engineering intelligent management has become an urgent need of the industry,and the premise of realizing engineering intelligent management is to realize the detection of engineering structural components.Therefore,in this paper,computer vision,deep learning,object recognition and other theories are applied to propose an efficient detection method for engineering structural component entities,aiming at solving the problem of engineering structural component detection and promoting the realization of engineering intelligent management.This paper mainly studies the automatic detection and simulation of structural components of building engineering from the following aspects.Firstly,this paper reviews many relevant domestic and foreign literatures from the perspective of status of engineering identification and detection technology.Then,the paper analyzes the feature information from the classification,geometry and spatial relation of engineering structural components.A fter clarifying the feature information of the research object,this paper starts from computer vision theory,combines the emerging field of deep learning and object detection,discusses the automatic detection method suitable to the building entity structural components,and proposes a new method for engineering structural components detection based on DSOD.To verify the effectiveness of the proposed method.based on the 1:20 architectural scale ratio model,the combination image dataset of engineering structural components is established through multi-layer,multi-state,multi-directional,multi-angle structural data acquisition,and the structural component detection accuracy and recall rate were tested under different shooting angles,different visual ranges and different occlusion levels.High precision and high recall rate indicate that the method can be effectively used to detect building structural components.On this basis,this paper constructs an automatic detection system for structural components of.construction engineering.Finally,this paper summarizes the work and the contribution of this research,and puts forward some suggestions for future research directions.This paper proposes new ideas for the detection of structural components in building entity images by using emerging technologies,which provides an important opportunity to detect strectural components m real time on the construction site and to promote the realization of' a new framework for automated analysis of blilding activities based on visual data.Moreover,the experimental results show that the method has high detection precision,high recall rate and high speed,which can ef-fectively solve the detection problem of engineering structural components,and is conducive to promotine the realization of intelligent project management.