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.

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.

Dam Deformation Monitoring and Data Analysis Based on Cloud Model

2012 ◽  
Vol 459 ◽  
pp. 479-482 ◽  
Author(s):  
Teng Jun Wang ◽  
Bo Yang ◽  
Hai Yan Yang
Keyword(s):  
Data Analysis ◽  
Quantitative Analysis ◽  
Qualitative Analysis ◽  
Cloud Model ◽  
Scientific Data ◽  
Deformation Monitoring ◽  
Monitoring Data ◽  
Monitoring Method ◽  
Reliable Monitoring ◽  
Dam Deformation

Dam deformation monitoring plays an important role in order to ensure the safety of dam operation, to improve project efficiency and the level of design and construction. Reliable monitoring method and scientific data analysis is the best protection for control the deformation law. Mathematical methods have been used to precisely quantitative analysis the deformation of the dam monitoring points. Usually, when assess the stability of deformation and evaluate the monitored data, qualitative languages are used to analyze qualitative result. The article combines cloud model with reliable monitoring data of Xiaolangdi to try to make qualitative analysis result quantitatively, and the quantitative analysis result can verify the qualitative analysis conclusion. It has realized the change between those two analyses. Also, utilize cloud model to analyzing deformation monitoring data is verified reliable.

scholarly journals A Prediction Model of Structural Settlement Based on EMD-SVR-WNN

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xianglong Luo ◽  
Wenjuan Gan ◽  
Lixin Wang ◽  
Yonghong Chen ◽  
Xue Meng
Keyword(s):  
Prediction Model ◽  
Prediction Accuracy ◽  
Deformation Monitoring ◽  
Monitoring Data ◽  
Structural Deformation ◽  
Random Fluctuation ◽  
Structural Safety ◽  
Support Vector ◽  
Foundation Pit ◽  
Deformation Prediction

Timely and accurate prediction of structural settlement is of great significance to eliminate the hidden danger of structural and prevent structural safety accidents. Since the deformation monitoring data usually is nonstationary and nonlinear, the deformation prediction is a difficult problem in the structural monitoring research. Aiming at the problems in the structural deformation prediction model and considering the internal characteristics of deformation monitoring data and the influence of different components in the data on the prediction accuracy, a combined prediction model based on the Empirical Mode Decomposition, Support Vector Regression, and Wavelet Neural Network (EMD-SVR-WNN) is proposed. EMD model is used to decompose the structure settlement monitoring data, and the settlement data can be effectively divided into relatively stable trend terms and residual components of random fluctuation by energy matrix. According to the different characteristics of random items and trend items, WNN and SVR methods are, respectively, used for prediction, and the final settlement prediction is obtained by integrating the prediction results. The measured ground settlement data of foundation pit in subway construction is used to test the performance of the model, and the test results show that the prediction accuracy of the combined prediction model proposed in this paper reaches 99.19%, which is 77.30% higher than the traditional SVR, WNN, and DBN-SVR models. The experimental results show that the proposed prediction model is an effective model of structural settlement.

scholarly journals Structural Safety Monitoring of High Arch Dam Using Improved ABC-BP Model

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Yantao Zhu ◽  
Chongshi Gu ◽  
Erfeng Zhao ◽  
Jintao Song ◽  
Zhiyun Guo
Keyword(s):  
Temporal Distribution ◽  
Safety Monitoring ◽  
Deformation Monitoring ◽  
Arch Dam ◽  
Monitoring Data ◽  
Structural Safety ◽  
Local Optimum ◽  
High Arch Dam ◽  
Monitoring Method ◽  
Monitoring Model

The establishment of a structural safety monitoring model of a dam is necessary for the evaluation of the dam’s deformation status. The structural safety monitoring method based on the monitoring data is widely used in traditional research. On the basis of the analysis of the high arch dam’s deformation principles, this study proposes a structural safety monitoring method derived from the dam deformation monitoring data. The method first analyzes and establishes the spatial and temporal distribution of high arch dam’s safety monitoring, overcoming the standard artificial bee colony (ABC) algorithm’s shortcoming of easily falling into the local optimum by adopting the adaptive proportion and average Euclidean distance afterwards. The improved ABC algorithm is used to optimize the backpropagation (BP) neural network’s initial weight and threshold. The application example proves that ABC-BP model’s improvement method is important for the establishment of a high arch deformation safety monitoring model and can effectively improve the model’s fitting and forecasting ability. This method provides a reference for the establishment of a structural safety monitoring model of dam and provides guidance for the establishment of a forecasting model in other fields.

Application of FBG Sensor in Shaft Structural Deformation Monitoring of JINCHUAN Mine No.3

2011 ◽  
Vol 243-249 ◽  
pp. 5420-5426 ◽  
Author(s):  
Zeng Hui Liu ◽  
Qian Gao ◽  
Zhi Qiang Yang
Keyword(s):  
Monitoring System ◽  
Practical Experience ◽  
Structural Condition ◽  
Deformation Monitoring ◽  
Reinforced Concrete Beams ◽  
Structural Deformation ◽  
Mine Shaft ◽  
Monitoring Method ◽  
Shaft Deformation

In order to effectively evaluate the security status of shaft and to make timely and accurate forecasts before the shaft break disaster, lead into fiber brag grating technology in the mine shaft deformation monitoring. Designing laboratory experiments verified FBG sensing the reliability of deformation and strain transfer law in reinforced concrete beams, while provide practical experience to the FBG sensors installed on the actual shaft structure. According to the structural condition of the main shaft of JINCHUAN Mine No.3, designed 8 monitoring sections in different level ingate upper and lower and installed fiber optic grating sensors, forming a fully automatic real-time and long-term deformation monitoring system. Initial monitoring results indicate that only the No.4 (down) sensors was failure, but the other seven monitoring sections can effectively detect the corresponding strain, and the monitoring system was stable. The fiber optical sensing technology has broad application prospects in the state's long-term monitoring deformation of the mine project, for the mine shaft deformation monitoring provides a more reliable monitoring method.

Deformation Monitoring and Data Analysis for Metro Construction with Mining Method in Dalian

2013 ◽  
Vol 353-356 ◽  
pp. 1604-1608
Author(s):  
Guang Bin Bai ◽  
Jie Zhao ◽  
Li Sheng Liu
Keyword(s):  
Data Analysis ◽  
Construction Method ◽  
Deformation Monitoring ◽  
Monitoring Data ◽  
Ground Subsidence ◽  
Tunnel Construction ◽  
Mining Method ◽  
Construction Process ◽  
Subway Tunnel ◽  
The Future

Based on a subway tunnel construction, the construction method was introduced. The ground subsidence, crown settlement and convergence displacement caused by the cut tunnel are monitored during the tunneling construction and the results of monitoring data for them are analyzed. This technology wells to guide the tunnel-entering construction effectively and avoid the tunnel-entering construction process prone to landslides, thus ensuring the safety of the tunnel construction and will guiding the future construction.

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 Analysis of temperature-induced deformation and stress distribution of long-span concrete truss combination arch bridge based on bridge health monitoring data and finite element simulation

2020 ◽  
Vol 16 (10) ◽  
pp. 155014772094520
Author(s):  
Yanwei Niu ◽  
Yong’e Wang ◽  
Yingying Tang
Keyword(s):  
Finite Element ◽  
Temperature Distribution ◽  
Stress Distribution ◽  
Health Monitoring ◽  
Three Dimensional ◽  
Monitoring Data ◽  
Temperature Fields ◽  
Structural Deformation ◽  
Arch Bridge ◽  
Bridge Health Monitoring

Through decades of operation, deformation fluctuation becomes a central problem affecting the normal operating of concrete truss combination arch bridge. In order to clarify the mechanism of temperature-induced deformation and its impact on structural stress distribution, this article reports on the temperature distribution and its effect on the deformation of concrete truss combination arch bridge based on bridge health monitoring on a proto bridge with 138 m main span. The temperature distribution and deformation characteristics of the bridge structure in deep valley area are studied. Both of the daily and yearly temperature variation and structural deformation are studied based on bridge health monitoring. Using the outcome of monitoring data, three-dimensional solid finite element models are established to analyze the mechanism of temperature-induced deformation of the whole bridge under different temperature fields. The influence of temperature-induced effect is discussed on local damage based on the damage observation of the background bridge. The outcome of comparisons with field observation validates the analysis results. The relevant monitoring and simulation result can be referenced for the design and evaluation of similar bridges.

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