Study On The Quality Control Of Underground Pipe Gallery Construction In Shenyang

Composed of underground structures and ancillary facilities,the urban underground integrated pipe gallery is for placing urban engineering pipelines.In recent years,although the scale of underground pipe gallery construction has been increasingly larger and faster in China,there is still a scarcity of studies on the quality control of underground pipe gallery construction.As the key to the success of a construction project,construction quality has drawn extensive attention all over the world.As the underground pipe gallery construction is complex and special,quality control is of the utmost importance.Therefore,the quality control of underground pipe gallery construction shall be intensified.However,at present,China's quality control mainly focuses on the on-going and completed construction,with a lack of pre-construction control.Therefore,it is especially important to establish a comprehensive quality control system.Based on the current status and development of quality control of pipe gallery at home and abroad,the importance of establishing a predictive model for the construction of pipe gallery is analyzed in this paper.Also,the BP neural network is introduced into the underground pipe gallery construction control,and therefore the quality of pipe gallery construction is controlled by collecting and analyzing the monitored data.BP neural network can cope with nonlinear,complex and big data analyses,thereby making up for the shortcomings of traditional construction quality control methods.A case study of the J25-J29 shield section of Shenyang underground integrated pipe gallery(south canal section)is conducted in this paper.The study is started with the five major factors affecting the shield construction quality control.Specifically,the main quality control points are selected;the construction quality control index system is determined;the underground pipe gallery construction quality control model is established based on BP neural network;the neural network model is realized with MATLAB,a numerical analysis software,and BP neural network.In doing so,the pre-construction quality can be well controlled.While establishing the construction quality control model,site investigation shall be conducted for data collection,thereby analyzing the change and development.Also,the comparison between the monitored settlement data and the settlement warning indicators shall be made,thereby proposing remedial measures or reinforcement measures that are aimed at the existing problems at the construction site or taking advanced construction techniques to improve the construction plan to well control on-going and completed construction.Pre-existing control,in-process control and post-event control are combined in this paper to research the quality control of underground pipe gallery construction in Shenyang.And it provides a new system for the quality control of underground pipe gallery construction and has certain application value.