scholarly journals Research and Application of a Smart Monitoring System to Monitor the Deformation of a Dam and a Slope

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yongfei Wang ◽  
Dingbin Shen ◽  
Jiankang Chen ◽  
Liang Pei ◽  
Yanling Li ◽  
...  
Keyword(s):  
Real Time ◽  
Mean Square Error ◽  
Monitoring System ◽  
Deformation Monitoring ◽  
Monitoring Data ◽  
Large Field ◽  
Maximum Relative Error ◽  
Mean Square ◽  
Integrated Monitoring ◽  
The Real

Deformation monitoring is one of the most important means of providing feedback to ensure the safety of projects. Problems plague the existing automatic monitoring system, such as the small monitoring range of monitoring devices, the inadequate field safety protection, and the low accuracy under extreme weather conditions. These problems greatly reduce the real time and reliability of deformation monitoring data and restrict the real-time intelligent control of engineering safety risk. In this paper, a multitype instrument-integrated monitoring system based mainly on the total positioning station (TPS) and supplemented by the Global Navigation Satellite System (GNSS) was promoted with the methods of large field angle, data complementation, environmental perception and judgment, automatic status control, and baseline calibration-meteorological fusion correction. The application results of Pubugou Station show that the averages of mean square error of points (APMSE) for the dam are 0.41∼1.65 mm and the averages of mean square error of height (AHMSE) are 0.42∼0.89 mm. Moreover, the APMSE and AHMSE for the slope are less than 3 mm. The maximum relative error of the TPS and GNSS data compared with the artificial monitoring data is less than 10%. Besides, the system has good overall performance and is of significant comprehensive benefits. The proposed system realizes the all-weather real-time monitoring of deformation and enhances the emergency response capability of special conditions in dams during the operation period.

scholarly journals Deformation Monitoring and Stability Analysis of Shaft Lining in Weakly Cemented Stratum

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Xianzhou Lyu ◽  
Weiming Wang
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Coal Mine ◽  
Deformation Monitoring ◽  
Dynamic Monitoring ◽  
Thick Wall ◽  
Additional Stress ◽  
The Real ◽  
Shaft Lining

Shaft linings in thick weakly cemented stratum have the disadvantages of large deformation and repeated damage after repair. Considering the typical geologic characteristics and the failure characteristics of shaft linings, we establish a multilayer automatic deformation monitoring system in this paper, and the monitoring system can realize the real-time, continuous, and long-term dynamic monitoring on shaft linings. Based on the concrete strength failure criterion under biaxial compression and the analytical solution for spatially axisymmetric problem of thick-wall cylinders, the damage limit of the shaft lining in Xieqiao coal mine is obtained. Then, we choose three sections as the test area according to the typical damage forms of shaft linings to carry out the monitoring scheme on the auxiliary shaft in Xieqiao coal mine. The monitoring results show that the extreme value of the shaft lining deformation is 2.369 mm. And the shaft lining located in the border between the floor aquifer and the bedrock generates the most severe deformation, which is about 89.4% of the deformation limit. The shaft lining deformation increment fluctuates in certain range, which belongs to elastic deformation. Finally, we inverse the stress state according to the deformation value of the shaft lining, and the obtained additional stress is found to be lower than the ultimate compressive strength. Long-term project practice confirms that the deformation monitoring results can reflect the real stress condition of the shaft lining and that the monitoring system can realize the real-time dynamic evaluation for the status of the shaft lining.

scholarly journals Development of Optic-Electric Hybrid Sensors for the Real-Time Intelligent Monitoring of Subway Tunnels

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Fu-guang Zhu ◽  
Dong-sheng Xu ◽  
Rui-shan Tan ◽  
Bin Peng ◽  
He Huang ◽  
...  
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Deformation Monitoring ◽  
Long Distance ◽  
Intelligent Monitoring ◽  
The Real ◽  
Laboratory Calibration ◽  
Hybrid Sensors ◽  
Subway Tunnels

The settlement and deformation monitoring of subway tunnels had difficult in long-distance and real time measurement. This study proposed an optic-electric hybrid sensor based on infrared laser ranging technology and cable-sensing technology. The working principle, hardware layer, design details, laboratory calibration and field validation were presented and discussed. The optic-electric hybrid sensor implemented the real-time intelligent analysis modulus for the whole system which could analysis the measurement errors and improve the accuracy. The laboratory calibration tests were carried out and the results shown that the hybrid sensors had measurement resolution of 1 mm with the maximum measurement range of 100 m. A remote real-time intelligent monitoring system is established based on the hybrid sensors. The system contains an edge computing module, real-time communication module and warning light signal with three colors. The stability of data acquisition and transmission of the intelligent control monitoring system under long-term conditions was examined. Test results shown that the system was quite stable for the long-term measurement. The whole system was verified in a constructing subway tunnel of Wuhan Metro Line 8, China. According to the field monitoring results, the deformations and the state of health safety of the tunnel was evaluated. The results of this study could provide useful guidance for tunnel deformation monitoring and has great practical value in civil engineering.

Outburst Hazard Prediction Based on the Monitoring Data in Heading Face

2013 ◽  
Vol 734-737 ◽  
pp. 786-790
Author(s):  
Fu Sheng Wu ◽  
Shui Wen Liu
Keyword(s):  
Mechanical Properties ◽  
Real Time ◽  
Monitoring System ◽  
Physical And Mechanical Properties ◽  
Monitoring Data ◽  
The Real ◽  
Verification Test ◽  
Outburst Hazard ◽  
Good Agreement ◽  
Predictive Indicators

To analyse the outburst hazard of heading face in real time, based on the mechanism of coal and gas burst and its forecasting principle, four real-time predictive indicators were proposed, which involve three aspects: crustal stress, gas, physical and mechanical properties of coal, and had a verification test. The results show that the real-time predictive indicators are in good agreement with the traditional indicators, whose deviation are mainly caused by gas exceeded. With the monitoring data in monitoring system, the outburst hazard of heading face could be predicted in real time, which could help to prevent outburst.

Intelligent Environmental Monitoring System Based on Multi-Sensor Data Technology

2020 ◽  
Vol 11 (4) ◽  
pp. 57-71
Author(s):  
Qiuxia Liu
Keyword(s):  
Data Fusion ◽  
Environmental Monitoring ◽  
Real Time ◽  
Monitoring System ◽  
Intelligent System ◽  
Evidence Synthesis ◽  
Environmental Parameters ◽  
Monitoring Data ◽  
Sensor Data ◽  
Environmental Monitoring System

Using multi-sensor data fusion technology, ARM technology, ZigBee technology, GPRS, and other technologies, an intelligent environmental monitoring system is studied and developed. The SCM STC12C5A60S2 is used to collect the main environmental parameters in real time intelligently. The collected data is transmitted to the central controller LPC2138 through the ZigBee module ATZGB-780S5, and then the collected data is transmitted to the management computer through the GPRS communication module SIM300; thus, the real-time processing and intelligent monitoring of the environmental parameters are realized. The structure of the system is optimized; the suitable fusion model of environmental monitoring parameters is established; the hardware and the software of the intelligent system are completed. Each sensor is set up synchronously at the end of environmental parameter acquisition. The method of different value detection is used to filter out different values. The authors obtain the reliability of the sensor through the application of the analytic hierarchy process. In the analysis and processing of parameters, they proposed a new data fusion algorithm by using the reliability, probability association algorithm, and evidence synthesis algorithm. Through this algorithm, the accuracy of environmental monitoring data and the accuracy of judging monitoring data are greatly improved.

scholarly journals Indian COVID-19 dynamics: Prediction using autoregressive integrated moving average modelling

2021 ◽  
Vol 52 (1) ◽  
pp. 6-14
Author(s):  
Amit Tak ◽  
Sunita Dia ◽  
Mahendra Dia ◽  
Todd Wehner
Keyword(s):  
Root Mean Square Error ◽  
Real Time ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Moving Average ◽  
Information Criteria ◽  
Evidence Based ◽  
Mean Square ◽  
Autoregressive Integrated Moving Average ◽  
Akaike Information Criteria

Background: The forecasting of Coronavirus Disease-19 (COVID-19) dynamics is a centrepiece in evidence-based disease management. Numerous approaches that use mathematical modelling have been used to predict the outcome of the pandemic, including data-driven models, empirical and hybrid models. This study was aimed at prediction of COVID-19 evolution in India using a model based on autoregressive integrated moving average (ARIMA). Material and Methods: Real-time Indian data of cumulative cases and deaths of COVID-19 was retrieved from the Johns Hopkins dashboard. The dataset from 11 March 2020 to 25 June 2020 (n = 107 time points) was used to fit the autoregressive integrated moving average model. The model with minimum Akaike Information Criteria was used for forecasting. The predicted root mean square error (PredRMSE) and base root mean square error (BaseRMSE) were used to validate the model. Results: The ARIMA (1,3,2) and ARIMA (3,3,1) model fit best for cumulative cases and deaths, respectively, with minimum Akaike Information Criteria. The prediction of cumulative cases and deaths for next 10 days from 26 June 2020 to 5 July 2020 showed a trend toward continuous increment. The PredRMSE and BaseRMSE of ARIMA (1,3,2) model were 21,137 and 166,330, respectively. Similarly, PredRMSE and BaseRMSE of ARIMA (3,3,1) model were 668.7 and 5,431, respectively. Conclusion: It is proposed that data on COVID-19 be collected continuously, and that forecasting continue in real time. The COVID-19 forecast assist government in resource optimisation and evidence-based decision making for a subsequent state of affairs.

Design of Embedded Video Monitoring System Based on DM6437

2014 ◽  
Vol 1003 ◽  
pp. 249-253
Author(s):  
Hao Fang ◽  
Ai Hua Li ◽  
Yan Fei Liu
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Transmission Function ◽  
Video Signal ◽  
Video Encoding ◽  
Video Monitoring ◽  
Time Requirement ◽  
The Real ◽  
Monitoring Platform

To solve the difficulty of traditional video monitoring system in system upgrade and expansion, an solution of embedded video monitoring system based on DaVinci technology was put forward in this paper. By building the monitoring platform by DM6437 and DSP/BIOS in the solution, TVP5151 was used for receiving video signal in PAL/NTSC formats, and an JPEG Baseline Profile Encoder was integrated for video encoding, and the 10/100M Ethernet transmission function was realized based on NDK. Finally, the system is tested and the result shows that the system can capture and transmit D1 format signal in 25f/s and met the real-time requirement. At the same time, the system is easy to use and expand with a bright application prospect.

Sign in / Sign up

Export Citation Format

Share Document