scholarly journals Goaf Locating Based on InSAR and Probability Integration Method

2019 ◽  
Vol 11 (7) ◽  
pp. 812 ◽  
Author(s):  
Sen Du ◽  
Yunjia Wang ◽  
Meinan Zheng ◽  
Dawei Zhou ◽  
Yuanping Xia
Keyword(s):  
Simulation Experiment ◽  
Real Data ◽  
Mining Area ◽  
Interferometric Synthetic Aperture Radar ◽  
Feature Points ◽  
Error Sources ◽  
Subsidence Basin ◽  
Inflection Points ◽  
Probability Integral Method ◽  
Relative Errors

Mining goafs can cause many hazards, such as burst water, spontaneous combustion of coal seams, surface collapse, etc. In this paper, a feature-points-based method for the efficient location of mining goafs is proposed. Different interferometric synthetic aperture radar (DInSAR) is used to monitor the subsidence basin caused by mining. Using the principles of the probability integral method (PIM), the inflection points and the boundary points of the basin monitored by DInSAR are determined and used as feature points to locate the goaf. In this paper, the necessity of locating goafs and the traditional methods used for this task are discussed first. Then, the results of verifying the proposed method by both a simulation experiment and real data experiment are presented. Six RADARSAT-2 images from 13th October 2015 to 5th March 2016 were used to acquire the subsidence basin caused by the 15235 working faces of the Jiulong mining area. The average relative errors of the simulation experiment and real data experiment were about 6.43% and 12.59%, respectively. The average absolute errors of the simulation experiment and real data experiment were about 28 m and 38 m, respectively. In the final part of this paper, the error sources are discussed to illustrate the factors that can affect the location result.

scholarly journals Three Dimensional Deformation of Mining Area Detection by InSAR and Probability Integral Model

2015 ◽  
Vol XL-7/W4 ◽  
pp. 23-26 ◽  
Author(s):  
H. D. Fan ◽  
X. X. Gao ◽  
D. Cheng ◽  
W. Y. Zhao ◽  
C. L. Zhao
Keyword(s):  
Three Dimensional ◽  
Mining Area ◽  
Integral Model ◽  
Subsidence Basin ◽  
Optimum Parameters ◽  
Probability Integral Method ◽  
Basin Edge ◽  
Probability Integral ◽  
Mining Work ◽  
Deformation Gradients

A new solution algorithm that combined D-InSAR and probability integral method was proposed to generate the three dimensional deformation in mining area. The details are as follows: according to the geological and mining data, the control points set should be established, which contains correct phase unwrapping points in subsidence basin edge generated by D-InSAR and several GPS points; Using the modulus method to calculate the optimum parameters of probability integral prediction; Finally, generate the three dimensional deformation of mining work face by the parameters. Using this method, the land subsidence with big deformation gradients in mining area were correctly generated by example TerraSAR-X images. The results of the example show that this method can generate the correct mining subsidence basin with a few surface observations, and it is much better than the results of D-InSAR.

scholarly journals 3D Mesh Pre-processing Method Based on Feature Point Classification and Anisotropic Vertex Denoising Considering Scene Structure Characteristics

2021 ◽  
Vol 13 (11) ◽  
pp. 2145
Author(s):  
Yawen Liu ◽  
Bingxuan Guo ◽  
Xiongwu Xiao ◽  
Wei Qiu
Keyword(s):  
Real Data ◽  
Geometric Constraints ◽  
Feature Point ◽  
Feature Points ◽  
Denoising Method ◽  
3D Mesh ◽  
Mesh Denoising ◽  
Scene Structure ◽  
Sharp Edges ◽  
Update Strategy

3D mesh denoising plays an important role in 3D model pre-processing and repair. A fundamental challenge in the mesh denoising process is to accurately extract features from the noise and to preserve and restore the scene structure features of the model. In this paper, we propose a novel feature-preserving mesh denoising method, which was based on robust guidance normal estimation, accurate feature point extraction and an anisotropic vertex denoising strategy. The methodology of the proposed approach is as follows: (1) The dual weight function that takes into account the angle characteristics is used to estimate the guidance normals of the surface, which improved the reliability of the joint bilateral filtering algorithm and avoids losing the corner structures; (2) The filtered facet normal is used to classify the feature points based on the normal voting tensor (NVT) method, which raised the accuracy and integrity of feature classification for the noisy model; (3) The anisotropic vertex update strategy is used in triangular mesh denoising: updating the non-feature points with isotropic neighborhood normals, which effectively suppressed the sharp edges from being smoothed; updating the feature points based on local geometric constraints, which preserved and restored the features while avoided sharp pseudo features. The detailed quantitative and qualitative analyses conducted on synthetic and real data show that our method can remove the noise of various mesh models and retain or restore the edge and corner features of the model without generating pseudo features.

scholarly journals Extraction of Irregularly Shaped Coal Mining Area Induced Ground Subsidence Prediction Based on Probability Integral Method

2020 ◽  
Vol 10 (18) ◽  
pp. 6623
Author(s):  
Xianfeng Tan ◽  
Bingzhong Song ◽  
Huaizhi Bo ◽  
Yunwei Li ◽  
Meng Wang ◽  
...  
Keyword(s):  
Coal Mining ◽  
Integral Method ◽  
Mesh Size ◽  
Mining Area ◽  
Ground Subsidence ◽  
Data Set ◽  
Coal Mining Area ◽  
Subsidence Prediction ◽  
Probability Integral Method ◽  
Probability Integral

Underground coal mining-induced ground subsidence (or major ground vertical settlement) is a major concern to the mining industry, government and people affected. Based on the probability integral method, this paper presents a new ground subsidence prediction method for predicting irregularly shaped coal mining area extraction-induced ground subsidence. Firstly, the Delaunay triangulation method is used to divide the irregularly shaped mining area into a series of triangular extraction elements. Then, the extraction elements within the calculation area are selected. Finally, the Monte Carlo method is used to calculate extraction element-induced ground subsidence. The proposed method was tested by two experimental data sets: the simulation data set and direct leveling-based subsidence observations. The simulation results show that the prediction error of the proposed method is proportional to mesh size and inversely proportional to the amount of generated random points within the auxiliary domain. In addition, when the mesh size is smaller than 0.5 times the minimum deviation of the inflection point of the mining area, and the amount of random points within an auxiliary domain is greater than 800 times the area of the extraction element, the difference between the proposed method-based subsidence predictions and the traditional probability integral method-based subsidence predictions is marginal. The measurement results show that the root-mean-square error of the proposed method-based subsidence predictions is smaller than 3 cm, the average of absolute deviations of the proposed method-based subsidence predictions is 2.49 cm, and the maximum absolute deviation is 4.05 cm, which is equal to 0.75% of the maximum direct leveling-based subsidence observation.

A Photographic Flux Mapping Method for Concentrating Solar Collectors and Receivers

2012 ◽  
Vol 134 (4) ◽  
Author(s):  
Clifford K. Ho ◽  
Siri S. Khalsa
Keyword(s):  
Digital Camera ◽  
Mapping Method ◽  
Test Facility ◽  
The Novel ◽  
Error Sources ◽  
Additional Information ◽  
Direct Normal Irradiance ◽  
Beam Characterization ◽  
Pixel Value ◽  
Relative Errors

A new method is described to determine irradiance distributions on receivers and targets from heliostats or other collectors for concentrating solar power applications. The method uses a digital camera, and, unlike previous beam characterization systems, it does not require additional sensors, calorimeters, or flux gauges on the receiver or target. In addition, spillage can exist and can also be measured (the beam does not need to be contained within the target). The only additional information required besides the images recorded from the digital camera is the direct normal irradiance and the reflectivity of the receiver. Methods are described to calculate either an average reflectivity or a reflectivity distribution for the receiver using the digital camera. The novel feature of this new photographic flux (PHLUX) mapping method is the use of recorded images of the sun to scale both the magnitude of each pixel value and the subtended angle of each pixel. A test was performed to evaluate the PHLUX method using a heliostat beam on the central receiver tower at the National Solar Thermal Test Facility in Albuquerque, NM. Results showed that the PHLUX method was capable of producing an accurate flux map of the heliostat beam on a Lambertian surface with a relative error in the peak flux of ∼2% when the filter attenuation factors and effective receiver reflectivity were well characterized. Total relative errors associated with the measured irradiance using the PHLUX method can be up to 20%–40%, depending on various error sources identified in the paper, namely, uncertainty in receiver reflectivity and filter attenuation.

A New High Precision Wide Area DGPS System

1997 ◽  
Vol 50 (1) ◽  
pp. 109-119
Author(s):  
V. Ashkenazi ◽  
C. H. J. Chao ◽  
W. Chen ◽  
C. J. Hill ◽  
T. Moore
Keyword(s):  
High Precision ◽  
Real Data ◽  
Wide Area ◽  
Accurate Estimation ◽  
Dual Frequency ◽  
Differential Gps ◽  
Positional Accuracy ◽  
Error Sources ◽  
Error Components ◽  
Atmospheric Propagation

This paper describes an advanced method, and the corresponding algorithms, which could provide a high precision Wide Area Differential GPS (WADGPS). The service would be suitable for single or dual frequency users, and could be introduced with very few reference stations. The two main components of the service are a precise, near real-time orbit determination of the GPS satellites, and an accurate estimation and modelling of ionospheric and tropospheric effects. Broad principles of the processing algorithms and results of both simulation and real data tests are described. User positioning accuracies of better than 2·5 m (r.m.s.) in plan and 3·0 m (r.m.s.) in height are achieved by both single and dual frequency scenarios.Wide Area Differential GPS (WADGPS) is being developed to overcome the main drawbacks of conventional or Local Area Differential GPS (LADGPS), where positional accuracy of a user degrades as the reference-to-user separation increases. The spatial decorrelation of the error sources, notably the atmospheric propagation and satellite orbital errors inherent in GPS, are the main causes of this accuracy degradation. Several organizations are involved in WADGPS research, and different conceptual approaches have been suggested. The proposed methods all share a common basic assumption: that the error sources which affect the system are broken down into individual error components and are modelled separately. The variance between the different techniques comes from the way in which the different error components are modelled.

scholarly journals A simple parametric representation of the Hodgkin-Huxley model

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254152
Author(s):  
Alejandro Rodríguez-Collado ◽  
Cristina Rueda
Keyword(s):  
Simulation Experiment ◽  
Reference Model ◽  
Real Data ◽  
Parametric Representation ◽  
Model Parameters ◽  
Cell Type ◽  
Machine Learning Methods ◽  
Primary Signal ◽  
Type Classification ◽  
Multicomponent Model

The Hodgkin-Huxley model, decades after its first presentation, is still a reference model in neuroscience as it has successfully reproduced the electrophysiological activity of many organisms. The primary signal in the model represents the membrane potential of a neuron. A simple representation of this signal is presented in this paper. The new proposal is an adapted Frequency Modulated Möbius multicomponent model defined as a signal plus error model in which the signal is decomposed as a sum of waves. The main strengths of the method are the simple parametric formulation, the interpretability and flexibility of the parameters that describe and discriminate the waveforms, the estimators’ identifiability and accuracy, and the robustness against noise. The approach is validated with a broad simulation experiment of Hodgkin-Huxley signals and real data from squid giant axons. Interesting differences between simulated and real data emerge from the comparison of the parameter configurations. Furthermore, the potential of the FMM parameters to predict Hodgkin-Huxley model parameters is shown using different Machine Learning methods. Finally, promising contributions of the approach in Spike Sorting and cell-type classification are detailed.

scholarly journals Application of Surface Deformation Monitoring in Mining Area by the Fusion of InSAR and Laser Scan Data

2015 ◽  
Vol XL-7/W4 ◽  
pp. 41-44
Author(s):  
J. L. Huang ◽  
K. Z. Deng ◽  
H. D. Fan ◽  
J. K. Yang
Keyword(s):  
Surface Deformation ◽  
Mining Area ◽  
Deformation Monitoring ◽  
Line Of Sight ◽  
Underground Coal Mining ◽  
Synthetic Aperture Radar Interferometry ◽  
Subsidence Basin ◽  
Digital Elevation ◽  
Scan Data ◽  
Elevation Model

Differential Synthetic Aperture Radar Interferometry (D-InSAR) as a new earth observation technique has become an important tool for monitoring ground movements caused by underground coal mining. However, the low resolution and accuracy of Digital Elevation Model (DEM) cause more error value of InSAR line-of-sight(LOS) surface deformation measurement. In this paper, a couple of Radarsat-2 and a pair of TerraSAR with SRTM, GDEM and LiDAR DEM are processed respectively to reveal the subsidence basin and the results have been compared each other. It illustrate that the accuracy of D-InSAR results been better improved by the high accuracy and resolution DEM.

scholarly journals InSAR monitoring surface deformation induced by underground mining using Sentinel-1 images

2020 ◽  
Vol 382 ◽  
pp. 237-240
Author(s):  
Ling Zhang ◽  
Daqing Ge ◽  
Xiaofang Guo ◽  
Bin Liu ◽  
Man Li ◽  
...  
Keyword(s):  
Land Subsidence ◽  
Surface Deformation ◽  
Underground Mining ◽  
Deformation Gradient ◽  
Mining Area ◽  
Interferometric Synthetic Aperture Radar ◽  
Mining Areas ◽  
Temporal Decorrelation ◽  
Land Deformation ◽  
Small Baseline

Abstract. Land subsidence can be caused by underground mining activities. Interferometric Synthetic Aperture Radar (InSAR) has became an economic, effective and accurate technique for land deformation survey and monitoring. In mining areas, there may be several factors to overcome for the succsessful application of InSAR, such as temporal decorrelation and detectable deformation gradient, that limit the ability of InSAR to monitoring rapid land subsidence. In this paper, images obtained by the Sentinel-1 satellite with 6 or 12 d revisiting time are used to improve the ability to detect a deformation gradient, and reduce the influence of temporal decorrelation. By combining Small Baseline Subsets (SBAS) and Interferometric Point Target Analysis (IPTA) methods, using the Nanhu mining area in Tangshan as an example, the spatial continuous results of land subsidence in this mining area are obtained with a 70 cm per year maximum rate, which clearly characterizes the deformation field and its deformation process. The results show that InSAR is a useful way to monitor land subsidence in a mining area and provides further data for environment mine restoration.

scholarly journals An Approach for Estimating Underground-Goaf Boundaries Based on Combining DInSAR with a Graphical Method

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Pu Bu ◽  
Chaokui Li ◽  
Mengguang Liao ◽  
Wentao Yang ◽  
Chuanguang Zhu ◽  
...  
Keyword(s):  
Graphical Method ◽  
Geophysical Methods ◽  
Measured Data ◽  
Synthetic Aperture ◽  
Basic Principles ◽  
Detection Range ◽  
Left Behind ◽  
Subsidence Basin ◽  
Basic Law ◽  
Relative Errors

The goaf left behind after mining has the potential to induce serious geological disasters due to the damaged internal structure of the rock. Estimating the boundary of the underground goaf can effectively control the occurrence of such disasters. However, traditional geophysical methods are inefficient and expensive and are particularly difficult to apply for a wide detection range. This paper proposes a new method for estimating the boundary of underground goaf using the differential interference synthetic aperture radar technique (DInSAR). More specifically, DInSAR is used to obtain the isoline of the subsidence basin above the goaf, and the direction of the two main sections of the goaf is then determined according to the basic law of mining subsidence. Following this, the basic principles of the probability integral and the graphical methods are combined to determine the mining boundary of the strike section and the incline section of the goaf. Finally, six geometric parameters reflecting the boundary of the goaf are obtained. Experiments on simulated and measured data indicate that the proposed method is feasible, with the average relative errors of the simulated and measured data reaching and maintained at 2.2% and 3.7%, respectively.

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