scholarly journals Multi-modal Landslide Monitoring Data Fusion Algorithm Based on Resistivity Imaging

2021 ◽  
Author(s):  
Haning Xu ◽  
Juzhi Deng ◽  
Xiaoqing Xu ◽  
Jian Zhang ◽  
Gang Li ◽  
...  
Keyword(s):  
Deformation Process ◽  
Deformation Monitoring ◽  
Monitoring Data ◽  
Landslide Monitoring ◽  
Layer By Layer ◽  
Semantic Matching ◽  
Imaging Data ◽  
Fusion Algorithm ◽  
Modal Data ◽  
Resistivity Imaging

Abstract In the process of landslide deformation monitoring, the indicators of monitoring system based on surface displacement cannot accurately reflect the deformation evolution law of deep geotechnical body. Although the joint time curve of deep displacement monitoring of borehole and related monitoring data can reflect the deformation characteristics inside the slope body, it cannot spatially describe and explain the overall deformation process of geotechnical body completely due to the limitation of technical conditions such as borehole. In this paper, using the characteristics of resistivity imaging technology with fast and accurate collection of electrical information of subsurface medium and multi-dimensional imaging, we take resistivity imaging data as complete modal data and fuse deep displacement and groundwater level and other modal data. Through joint depth matrix decomposition and optimization, layer-by-layer modal semantic matching and updating, the distribution and representation differences of modal data are compensated, and the analysis tasks such as classification and clustering of incomplete multimodal data are completed, and the inversion results of resistivity data are updated according to the output modal shared eigenvalues to realize effective multidimensional imaging monitoring of the internal deformation process of landslide geological bodies.

Deformation Monitoring Data De-Noising Processing Based on Wavelet Packet

2012 ◽  
Vol 166-169 ◽  
pp. 1180-1186 ◽  
Author(s):  
Yan Mei Yang ◽  
Ze Gen Wang ◽  
Yu Yun Gao ◽  
Fa Peng Gao
Keyword(s):  
Wavelet Packet ◽  
Low Frequency ◽  
Deformation Monitoring ◽  
Monitoring Data ◽  
Local Analysis ◽  
Landslide Monitoring ◽  
Minimum Entropy ◽  
Mathematical Methods ◽  
Lower Amplitude ◽  
Unbiased Risk

Wavelet packet coefficients carrying real signals have large amplitude but are in minority, while those carrying noise has lower amplitude but is of large number. In this case, the Basic principle of de-noising wavelet packet is to process signals carrying noise. A suitable threshold is chosen in different decomposition level. Wavelet packet coefficient of less than this threshold is set to equal zero, while wavelet packet coefficients of greater than this threshold is reserved and reconstructed into de-noising signals. MSE, SNR, PSNR are regarded as the standards of de-noising evaluation, some mathematical methods such as Shannon entropy, norm entropy, logarithm energy entropy, threshold entropy, Stein Unbiased Risk Estimate entropy are adopted to measure whether the wavelet packet basis is optimal , minimum Entropy function D value is the best base. Selecting threshold and threshold quantitative is the key to wavelet packet de-noising. And selection of threshold value abides standards such as Sqtwolog, Rigrsure, Heursure, Manimaxi, or Birge-massart. Wavelet packet de-noising method has been applied to tunnel vault sink and landslide monitoring data de-noising processing, which manifests itself being a more elaborate, flexible method compared to wavelet de-noising, since wavelet packet de-noising can even subdivided the low-frequency part and the high-frequency part of upper layer, thus entertains a more precise local analysis capabilities.

In-Process Visualisation for Deformation Monitoring and Analysis of Sheet Metal Forming Processes

2013 ◽  
Vol 677 ◽  
pp. 384-387 ◽  
Author(s):  
Wai Kei Ricky Kot ◽  
Luen Chow Chan
Keyword(s):  
Sheet Metal ◽  
Sheet Metal Forming ◽  
Deep Drawing ◽  
Metal Forming ◽  
Deformation Process ◽  
Deformation Monitoring ◽  
Displacement Sensor ◽  
Laser Displacement Sensor ◽  
Profile Data ◽  
Profile Change

In this paper, a visualisation system will be discussed that can be used to capture the deformation profile of the sheet blank during sheet metal forming processes, such as deep drawing and shape forming. The visualisation system utilizes a 2D laser displacement sensor for deformation profile acquisition. The sensor is embedded in the die and the laser propagates through the die to detect the profile change of the specimen concealed in the die during operation. The captured profile data will be collected, manipulated and transferred to a monitor for display via a controller. This visualisation of the deformation profile will provide engineers and researchers with an intuitive means of analysing and diagnosing the deformation process during sheet metal forming.

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.

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.

Knowledge-guided consistent correlation analysis of multimode landslide monitoring data

2017 ◽  
Vol 31 (11) ◽  
pp. 2255-2271
Author(s):  
Shuangxi Miao ◽  
Qing Zhu ◽  
Bo Zhang ◽  
Yuling Ding ◽  
Junxiao Zhang ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Monitoring Data ◽  
Landslide Monitoring

scholarly journals Experimental Study on Slope Deformation Monitoring Based on a Combined Optical Fiber Transducer

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Yong Zheng ◽  
Dong-Yan Liu ◽  
Zheng-Wei Zhu ◽  
Hong-Lin Liu ◽  
Bang Liu
Keyword(s):  
Optical Fiber ◽  
Empirical Formula ◽  
Large Scale ◽  
Base Material ◽  
Optical Loss ◽  
Deformation Monitoring ◽  
Landslide Monitoring ◽  
Sandy Clay ◽  
Measured Displacement ◽  
Clay Slopes

Landslide monitoring is very important in predicting the behavior of landslides, thereby ensuring environment, life, and property safety. On the basis of our previous studies, a novel combined optic fiber transducer (COFT) for landslides monitoring and the related analysis methods are presented. Based on the principles of optical fiber microbending loss, the empirical formula of the shearing displacement of sliding body versus optical loss was established through a stretching test of optical fiber bowknot. Then the COFT grouting direct shearing tests, a large-scale landslide model test, and numerical modeling verification with FLAC3D are carried out. According to the results, the initial measurement precision of the designed COFT in sandy clay is 1 mm; its monitoring sliding distance is larger than 26.5 mm. The calculated values based on empirical formula are in good agreement with the laboratory tests and numerical simulation results. When the ratio of cement and sand in mortar is 1 : 5, the error between the calculated displacement and the measured displacement of sliding surface is the smallest. The COFT with expandable polystyrene (EPS) as its base material performs better in monitoring sandy clay slopes because both the error and the mean square deviation of the empirical formula are smaller.

Study on the Information Processing Technology of Deformation Monitoring Data in the Underground Engineering

2013 ◽  
Vol 353-356 ◽  
pp. 1555-1558
Author(s):  
Ke Wu ◽  
Ke Zhang ◽  
Cheng Jun Wang ◽  
Chuang Zhao
Keyword(s):  
Data Processing ◽  
Measurement Data ◽  
Processing System ◽  
Deformation Monitoring ◽  
Surrounding Rock ◽  
Monitoring Data ◽  
Dynamic Monitoring ◽  
Information Control ◽  
Underground Engineering ◽  
Engineering Construction

The deformation monitoring of surrounding rock and data processing in tunnel is the foundation and safety technical support of underground engineering information control and management. However, due to the special environment in the underground engineering construction, acquiring the deformation information of surrounding rock accurately and fast to assess the stability of surrounding rock is becoming one of the bottleneck problems for underground construction project information to be solved. According to the underground engineering projects, Based on the dynamic monitoring data processing and analysis, a set of underground engineering construction monitoring measurement data processing system is established, which can meet the acquisition of the monitoring measurement data, the arrangement of the measured data, data analysis and feedback, the monitoring data regression analysis.

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