scholarly journals Deformation Detection Model of High-Rise Building Foundation Pit Support Structure Based on Neural Network and Wireless Communication

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Diandian Ding

The reasonable selection and optimized design of the deep foundation pit support scheme is directly related to the safety, construction period, and cost of the entire project. Here, based on a large number of theoretical results in many related fields, relevant influencing factors are systematically analyzed, and advanced mathematical algorithms such as neural networks are introduced according to the relevant characteristics of building deep foundation pit support construction. First of all, this paper designs and implements deep foundation pit construction safety risk technology based on wireless communication and BIM technology and analyzes and describes the framework and function of the foundation pit construction safety risk identification system. Secondly, we use neural network algorithms to study the deformation prediction of the foundation pit supporting structure, which can describe the expression method of the above safety knowledge. Finally, the differences and benefits of this method and traditional methods are compared through experiments, which show that this technology can pave the way for the construction of deep foundation pit construction safety risk knowledge.

2013 ◽  
Vol 671-674 ◽  
pp. 113-116
Author(s):  
Chun Yuan Liu ◽  
Wei Wei Cao ◽  
Yu Liu

Based on the impact of deep foundation pit excavation to the adjacent history style construction, FLAC3D was adopted to establish the excavation and supporting calculation model of a pit in Tianjin. The excavation deformation was analyzed, and the contact slip effect of the supporting structure and soil was considered. The results of study are as follows. (1) The pit has been dig to the third layer, and the values calculated are consistent with the monitored ones by comparing simulation values and measured results on B1 section. (2) Digging to the bottom of the pit, we can predict the biggest horizontal displacement of soil is 34.6 mm, and the value is 11.2mm in the history style construction. Therefore, the results of the study can play a guiding role in the engineering construction safety.


2012 ◽  
Vol 446-449 ◽  
pp. 1775-1780
Author(s):  
Jian Xin Zhang ◽  
Jia Li Dai ◽  
Bin Liu

Based on the monitoring data of the deep foundation pit, established an adjacent deep foundation pit safety risk fuzzy synthetic evaluation model, and then determine safety grades , using the method to evaluate the safety of the environment surrounding the foundation pit. Practice proves that the method can reflect the risk condition of the pit, and provided a new way to check the security of the pit.


2014 ◽  
Vol 697 ◽  
pp. 530-534
Author(s):  
Yu Bo Hu ◽  
Fei Shao ◽  
Ya Xin Huang ◽  
Ya Wen Liu ◽  
Jin Jun Liang

The prediction of deformation of foundation pit’s supporting structure is the basis of construction control of deep foundation pit. Meanwhile, it is vital to the safe excavation of foundation pit. In the work, the 1st project of Huaqiao in Jiantao Square of Kunshan City is chosen. Besides, model of combination based on entropy method is built to predict the displacement of circle beam with BP neural network and ARMA time series model. Finally, the analysis shows that combination models improve overall prediction on the premise of better predicting accuracy. Thus, it is of practical value.


2021 ◽  
Vol 233 ◽  
pp. 03001
Author(s):  
Xie Xiudong ◽  
Pan Caizhen

The monitoring data can effectively reflect the safety status of the project during the construction of deep foundation pit, and the risks existing in the project can be discovered in time and the development trend can be reasonably predicted through the processing and analysis of the existing monitoring data. In this paper, a deep foundation pit in compound soil area of a coastal city was taken as an example, the BP neural network was taken to predict the monitoring data in the next stage, the entropy method was utilized to determine the weight of the evaluation index according to the predicted value, and the fuzzy comprehensive evaluation method was used to quantitatively describe the future safety status, so as to formulate targeted countermeasures and improve the construction safety.


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