scholarly journals Geographic mapping model for underground structural deformation monitoring

2013 ◽  
Vol 5 (4) ◽  
pp. 353-372
Author(s):  
Wei Zheng ◽  
Yinsheng Li ◽  
Qi Lu ◽  
Ping Lu
Keyword(s):  
Deformation Monitoring ◽  
Structural Deformation ◽  
Mapping Model ◽  
Geographic Mapping

Ultrasonic Transceiver-Based Structural Deformation Monitoring with Location Ability

2014 ◽  
Vol 721 ◽  
pp. 442-445
Author(s):  
Wei Zheng ◽  
Chun Xian Wu ◽  
Rong Rong Cui
Keyword(s):  
Spatial Relations ◽  
Deformation Monitoring ◽  
Monitoring Data ◽  
Structural Deformation ◽  
Monitoring Method ◽  
Regional Monitoring ◽  
Space Deformation ◽  
Structural Surface

Regional coverage monitoring for structural deformation remains a challenge for current technologies. A coverage regional monitoring method based on dual ultrasonic transceivers and exhibiting deformation location ability is presented. The spatial projecting model of dual ultrasonic beams is established to determine the monitoring scope of the structural surface in space. Deformation location principles are induced by analyzing the spatial relations of the monitoring data of dual ultrasonic transceivers. Finally, an experiment is proposed to illustrate the method.

Accuracy of Static Differential GPS Techniques; Implications for Structural Deformation Monitoring

2009 ◽  
Vol 62-64 ◽  
pp. 31-38
Author(s):  
J.O. Ehiorobo
Keyword(s):  
Carrier Phase ◽  
Reference Frames ◽  
Phase Measurement ◽  
Sampling Rate ◽  
Tall Buildings ◽  
Deformation Monitoring ◽  
Structural Deformation ◽  
Control Network ◽  
Differential Gps ◽  
Engineering Structures

In recent years, the need to monitor for Deformation in Engineering Structures such as Dams, Bridges and Tall buildings have become more necessary as a result of reported failures of many of these structures with catastrophic consequences globally. Global Positioning System (GPS) is highly automated and less labour intensive than other conventional techniques used in structural deformation monitoring. For most applications, such as National Geodetic Control Network, Urban Control Network and other Engineering Control Network, an accuracy in the cm level for most GPS work is quite adequate. For Structural deformation monitoring however, the required accuracy is in millimeters. In this paper, the use of Static Differential GPS method with multiple receivers for high precision measurement was investigated using the monitoring Stations at Ikpoba Dam as case study Scenerio. Four units of LEICA 300 Dual Frequency GPS receivers were deployed for code and carrier phase measurements with observation session of 1hr at a sampling rate of 15 sec. Baseline Processing and Least Squares Adjustment of observation was carried out in WGS 84 and NTM reference frames using the LEICA SKI-PRO Processing software and Move. Analysis of the results revealed that the number of outliers in the observation were <5% and the accuracy of horizontal and vertical coordinates were 4mm maximum for horizontal and 2mm maximum for vertical. The study revealed that in areas with favourable satellite constellation and appropriate reduction or elimination of multipath and other noise like errors, Static Differential GPS techniques with a combination of code and carrier phase measurement gives good results for structural deformation monitoring.

scholarly journals Safety Management System Prototype/Framework of Deep Foundation Pit Based on BIM and IoT

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Wenhan Fan ◽  
Jianliang Zhou ◽  
Jianming Zhou ◽  
Dandan Liu ◽  
Wenjing Shen ◽  
...  
Keyword(s):  
Management System ◽  
Safety Management ◽  
Deformation Monitoring ◽  
Structural Deformation ◽  
Underground Construction ◽  
Construction Sites ◽  
Deep Foundation ◽  
Foundation Pit ◽  
Safety Management System ◽  
Deep Foundation Pit

With the huge demand for building underground spaces, deep foundation pits are becoming more and more common in underground construction. Due to the serious effects associated with accidents that occur in deep foundation pits, it is very important for underground construction safety management to be proactive, targeted, and effective. This research develops a conceptual framework adopting BIM and IoT to aid the identification and evaluation of hazards in deep foundation pit construction sites using an automated early warning system. Based on the accident analysis, the system framework of Safety Management System of Deep Foundation Pits (SMSoDFP) is proposed; it includes a function requirement, system modules, and information needs. Further, the implementation principles are studied; they cover hazardous areas, namely, visualization, personnel position monitoring, structural deformation monitoring, and automatic warning. Finally, a case study is used to demonstrate the effectiveness and feasibility of the system proposed. This research provides suggestions for on-site management and information integration of deep foundation pits, with a view to improving the safety management efficiency of construction sites and reducing accidents.

scholarly journals Gray relational analysis between the maglev-structural deformation and construction parameters of the shield tunnel crossing the shanghai maglev protected area

2018 ◽  
Vol 4 (4) ◽  
pp. 146-156 ◽  
Author(s):  
Guo-Qiang Wang ◽  
Song-Tao Hu ◽  
Guo-Feng Zeng ◽  
Feng Ye ◽  
Wen-Li Zu
Keyword(s):  
Protected Area ◽  
High Speed ◽  
Deformation Monitoring ◽  
Parameters Optimization ◽  
Structural Deformation ◽  
Gray Relational Analysis ◽  
Shield Tunnel ◽  
Maglev Train ◽  
Relational Analysis ◽  
Gray Relation Analysis

Background: Shanghai Maglev Demonstration Line is the only commercial high-speed maglev train line in the world, which has multiple functions such as transportation, exhibition, tourism and sightseeing. Besides, Shanghai Maglev Demonstration Line has been in operation for 15 years, and has been operating safely and punctually. Maglev protected area are located within 30 meters of the left and right sides of the Shanghai Maglev Demonstration Line and unrelated persons are not allowed to enter the area. When there were external construction invading the protected area, it is neccessary to do the comprehensive technical monitoring and protection. Without similar project to refer to, Metro Line 13 traversing Shanghai Maglev Line was a big challenge. Therefore, effective measures should be taken to do the comprehensive technical monitoring. Finding the relation between the maglev deformation and shield construction parameters was an important part of the monitoring. Aim: This thesis aimed at finding the relation between the maglev deformation and shield construction parameters and controlling the maglev deformation in the crossing of Metro Line 13, thus guiding the shield construction. Methods: This thesis calculated the gray relation between the maglev deformation and shield construction parameters from the cause of deformation of the maglev by the gray relation analysis. Results: The construction parameters optimization and the sensitivity control are carried out. Meanwhile, combined with the measured results of deformation monitoring, the multi means parallel monitoring data are analyzed synthetically and the data are checked, and the construction parameters are adjusted reasonably to make the pier column deformation in the controllable permissible range, having ensured the safe operation of the maglev. Conclusion: The calculation results has provided a reference for realizing active control on the influence of shield construction on the maglev and has remedied the defect that could only use deformation monitoring but could not control the deformation actively in the past work. The gray relational analysis has a certain effect on controlling the influence of shield construction on surrounding structures and has certain reference significance for subsequent similar projects.

Study on the Structural Deformation Monitoring Based on Distributed FBG Sensing Techniques

2013 ◽  
Vol 330 ◽  
pp. 389-395
Author(s):  
Cai Qian Yang ◽  
Ye Fei Xia ◽  
Zi Yan Chen ◽  
Wan Hong ◽  
Zhi Shen Wu
Keyword(s):  
Health Monitoring ◽  
Deformation Monitoring ◽  
Structural Deformation ◽  
Rc Beam ◽  
Strain Sensing ◽  
Four Point Bending ◽  
Beam Method ◽  
Step Loading ◽  
Distributed Strain ◽  
Dial Gauge

The deformation is an important parameter in structural health monitoring, and a conjugate beam method based on long-gauge fiber Bragg grating distributed strain sensing techniques is proposed to obtain the deformation of a structure. Some experiments are carried out to study the accuracy of this method using a four point bending RC beam under a step loading manner. The deformation obtained with the proposed method agrees well with those obtained with the conventional dial gauge in low loading steps. In addition, some measure is put forward to calibrate the proposed method and improve its accuracy at high loading steps, especially after the initiation of concrete cracks.

Application and Research of 3D Laser Scanning Technology in Steel Structure Installation and Deformation Monitoring

2014 ◽  
Vol 580-583 ◽  
pp. 2838-2841 ◽  
Author(s):  
Dong Ling Ma ◽  
Jian Cui ◽  
Shi Yan Wang
Keyword(s):  
Quality Control ◽  
Laser Scanning ◽  
Steel Structure ◽  
Deformation Monitoring ◽  
Structural Deformation ◽  
Laser Radar ◽  
Measurement Technology ◽  
Feature Points ◽  
Cloud Data ◽  
Large Span

The traditional steel structure deformation monitoring generally uses Total Station and GPS to do monitoring quality control, but there are some disadvantages of these methods. Laser radar technology is a new non-contact measurement technology emerged in recent years. It is ideal for installation and slip construction quality monitoring of large-span steel structure. This paper use laser radar technology to monitor large-span steel structure construction, use laser scanner to scan on steel every period of time and collect 3D point cloud data of the feature points after a period of time. Through the comparative analysis of the data and the chart which reflect the amount of deformation of the feature points, it can accurately obtain the result of structural deformation, oblique direction, and the deviation between the actual coordinates and the design coordinates, which provides the most accurate and direct information for the project. Laser radar technology solves the difficult issues such as workload outside the industry and difficulties in visibility of the traditional measurement methods, greatly improves accuracy and efficiency compared to traditional methods, and achieve a high-precision quality control over the construction.

scholarly journals An Overall Deformation Monitoring Method of Structure Based on Tracking Deformation Contour

2019 ◽  
Vol 9 (21) ◽  
pp. 4532 ◽  
Author(s):  
Xi Chu ◽  
Zhixiang Zhou ◽  
Guojun Deng ◽  
Xin Duan ◽  
Xin Jiang
Keyword(s):  
Edge Detection ◽  
Orthogonal Projection ◽  
Perspective Transformation ◽  
Deformation Monitoring ◽  
Structural Deformation ◽  
Health State ◽  
Test Beam ◽  
Monitoring Method ◽  
Projection Image ◽  
Complete Deformation

In structural deformation monitoring, traditional methods are mainly based on the deformation data measured at several individual points. As a result, only the discrete deformation, not the overall one, can be obtained, which hinders the researcher from a better and all-round understanding on the structural behavior. At the same time, the surrounding area around the measuring structure is usually complicated, which notably escalates the difficulty in accessing the deformation data. In dealing with the said issues, a digital image-based method is proposed for the overall structural deformation monitoring, utilizing the image perspective transformation and edge detection. Due to the limitation on camera sites, the lens is usually not orthogonal to the measuring structure. As a result, the obtained image cannot be used to extract the deformation data directly. Thus, the perspective transformation algorithm is used to obtain the orthogonal projection image of the test beam under the condition of inclined photography, which enables the direct extraction of deformation data from the original image. Meanwhile, edge detection operators are used to detect the edge of structure’s orthogonal projection image, to further characterize the key feature of structural deformation. Using the operator, the complete deformation data of structural edge are obtained by locating and calibrating the edge pixels. Based on the above, a series of load tests has been carried out using a steel–concrete composite beam to validate the proposed method, with the implementation of traditional dial deformation gauges. It has been found that the extracted edge lines have an obvious sawtooth effect due to the illumination environment. The sawtooth effect makes the extracted edge lines slightly fluctuate around the actual contour of the structure. On this end, the fitting method is applied to minimize the fluctuation and obtain the linear approximation of the actual deflection curve. The deformation data obtained by the proposed method have been compared with the one measured by the dial meters, indicating that the measurement error of the proposed method is less than 5%. However, since the overall deformation data are continuously measured by the proposed method, it can better reflect the overall deformation of the structure, and moreover the structural health state, when compared with the traditional “point” measurements.

scholarly journals A Deep Learning Prediction Model for Structural Deformation Based on Temporal Convolutional Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xianglong Luo ◽  
Wenjuan Gan ◽  
Lixin Wang ◽  
Yonghong Chen ◽  
Enlin Ma
Keyword(s):  
Prediction Model ◽  
Structural Engineering ◽  
Orthogonal Experiment ◽  
Deformation Monitoring ◽  
Structural Deformation ◽  
Long Term Memory ◽  
Model Parameters ◽  
Deformation Prediction ◽  
Convolutional Networks ◽  
Proposed Model

The structural engineering is subject to various subjective and objective factors, the deformation is usually inevitable, the deformation monitoring data usually are nonstationary and nonlinear, and the deformation prediction is a difficult problem in the field of structural monitoring. Aiming at the problems of the traditional structural deformation prediction methods, a structural deformation prediction model is proposed based on temporal convolutional networks (TCNs) in this study. The proposed model uses a one-dimensional dilated causal convolution to reduce the model parameters, expand the receptive field, and prevent future information leakage. By obtaining the long-term memory of time series, the internal time characteristics of structural deformation data can be effectively mined. The network hyperparameters of the TCN model are optimized by the orthogonal experiment, which determines the optimal combination of model parameters. The experimental results show that the predicted values of the proposed model are highly consistent with the actual monitored values. The average RMSE, MAPE, and MAE with the optimized model parameters reduce 44.15%, 82.03%, and 66.48%, respectively, and the average running time is reduced by 45.41% compared with the results without optimization parameters. The average RMSE, MAE, and MAPE reduce by 26.88%, 62.16%, and 40.83%, respectively, compared with WNN, DBN-SVR, GRU, and LSTM models.

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