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 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.

scholarly journals Probability Integral Method Parameter Determination by SBAS-InSAR Technology and GWO Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Tieming Liu ◽  
Tongkang Zhang ◽  
Lichuan Chen ◽  
Weiming Liao ◽  
Yun Shi ◽  
...  
Keyword(s):  
Integral Method ◽  
Fitness Function ◽  
Absolute Error ◽  
Mining Area ◽  
Maximum Absolute Error ◽  
Working Face ◽  
Probability Integral Method ◽  
Median Error ◽  
Probability Integral ◽  
Sbas Insar

This paper proposed a method based on the SBAS-InSAR and gray wolf optimization algorithm aiming at the time-consuming and laborious defects of the traditional method used to obtain the expected parameters of the probability integral method and the shortcomings of the InSAR technology in the field of large gradient deformation detection in the mining area. The fitness function of the algorithm was established based on the geometric relationship between the radar side imaging and the three-dimensional model of the probability integral method. The stable sinking point of the settlement boundary obtained by SBAS-InSAR was used as the input value for the calculation of the predicted parameters of the probability integral method. Firstly, the simulation experiment was employed for the simulation of the direction of the InSAR line of sight combined with the geological mining conditions of the assumed working face, thereby obtaining the probability integral prediction parameters of the working face. Consequently, the maximum relative error of q , b , tanβ, and θ 0 does not exceed 8%, and that of S 1 , S 2 , S 3 , and S 4 does not exceed 35.5% (low parameter sensitivity). The error of the LOS-direction deformation fitting is 0.076 m, which meets the tolerance requirements, and the result is trustworthy. At last, the parameter finding method is applied to the engineering example, that is, the 112201 working face of Xiaobaodang Coal Mine in the northern Shaanxi mining area. The settlement value of the stable boundary point is obtained based on the SBAS-InSAR results, which is substituted into the fitness function. And the GWO optimization algorithm is used for optimization and parameter finding; the probability integral expected parameters of the working face are calculated as q = 0.63 , b = 0.37 , tan β = 2.76 , θ 0 = 83.94 , S 1 = − 36.34   m , S 2 = 26.69   m , S 3 = − 45.64   m , and S 4 = 39.62   m . Substitute the obtained parameters into the probability integral model for the prediction of the vertical and horizontal displacements of the working face, and verify its accuracy with the GPS measured data. The results showed that the maximum absolute error of vertical displacement reached 116 mm, the median error was 63 mm, and the maximum absolute error of north-south horizontal movement reached 56 mm; meanwhile, the median error was 23 mm, the maximum absolute error of east-west horizontal movement reached 61 mm, and the median error was 29 mm; all the above parameters are within the tolerance range, indicating that the method for the calculation of probability integral parameters proposed in this paper is applicable in actual engineering.

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.

Three-Dimensional Simulations of Strong Ground Motion in the Shidian Basin

2014 ◽  
Vol 501-504 ◽  
pp. 1447-1452
Author(s):  
Yan Yan Yu ◽  
Qi Fang Liu
Keyword(s):  
Surface Wave ◽  
Ground Motion ◽  
Seismic Waves ◽  
Three Dimensional ◽  
Spectral Element ◽  
Low Velocity ◽  
Computing Technique ◽  
Soil Deposits ◽  
Basin Edge ◽  
The Impact

Seismic response of the Shidian basin to moderate scenario earthquake is investigated considering 3D basin model incorporated with real topography by using the spectral-element method and parallel computing technique. The wave propagation process, the generation of surface wave, and the impact of soil deposits velocity to the basin-induced surface wave are studied in this paper. The results show that the amplification behavior of the basin is the interactions of basin geometry and low velocity soil deposits. First, locally small hollows in the basin are apt to trap seismic waves and produce much stronger ground motion, basin edge and areas with deep sediments are also characterized with large amplification. Then, basin with softer soil deposits produces stronger surface waves with lower propagation velocity and higher mode.

scholarly journals Rational size and stability analysis of horizontal isolated pillars in deep mining from caving to filling method

2021 ◽  
Vol 303 ◽  
pp. 01040
Author(s):  
Fan Feng ◽  
Xibing Li ◽  
Shaojie Chen ◽  
Dingxiao Peng ◽  
Zhuang Bian
Keyword(s):  
Numerical Simulation ◽  
Three Dimensional ◽  
Mining Area ◽  
Middle Section ◽  
Deep Mining ◽  
Metal Mines ◽  
Lead Zinc ◽  
Filling Method ◽  
Zinc Mine ◽  
Cut And Fill

For mining using the caving and filling methods in metal mines, determining a suitable size for the isolated pillars—the connecting part of the extension from shallow to deep—is crucial for ensuring safety and efficiency. Considering actual cases involving deep caving and cut-and-fill mining in the Chifeng Hongling lead-zinc mine in Inner Mongolia, China, the reserved thickness range of the horizontal isolation layer is obtained via theoretical analysis. On this basis, the pre-processing software HyperMesh is used to build a high-precision hexahedral grid model of the mining area, and the three-dimensional geological model of the mining area is imported into the finite-difference software FLAC3D. The stress field, displacement field, and plastic area evolution law of pillars (horizontally isolated pillars and adjacent rib pillars) in the stope of the ninth middle section after excavation are analyzed via numerical simulation inversion of the selected scheme of horizontal isolated pillars. The numerical simulation results show that the scheme employed to retain the upper horizontal isolated pillars in the ninth middle section involves reserving thicknesses of 8 m and 32 m at average ore body thicknesses of 15 m and 35 m, respectively. These results can provide theoretical guidance and a basis for safe and efficient mining of deep metal mines.

Experimental Investigation of Strengthening and Polishing Aeroengine Blades

2011 ◽  
Vol 101-102 ◽  
pp. 909-912
Author(s):  
Guo Ying Zeng ◽  
Deng Feng Zhao
Keyword(s):  
Surface Roughness ◽  
Experimental Investigation ◽  
Fatigue Strength ◽  
Surface Quality ◽  
Three Dimensional ◽  
Experimental Results ◽  
Technological Parameters ◽  
Polishing Process ◽  
Optimum Parameters ◽  
The Media

The three-dimensional vibratory strengthening and polishing technology was used to strengthen and polish aeroengine blades with complicated surfaces. At first, the principle of the strengthening and polishing process was introduced, which combined strengthening process with polishing process. Then, the technological parameters influenced on the surface quality were investigated. The principal variables were the media hardness, the frequency and amplitude of the vibration, and duration of the vibratory strengthening and polishing. The optimum parameters were obtained. Experimental results revealed that, after strengthening and polishing, the surface roughness of aeroengine blades was reduced from Ra0.35-0.5μm to Ra0.1-0.12μm, and fatigue strength was increased by approximately 50%.

Robust estimation of model parameters of the probability integral method based on CA-rPSO

Survey Review ◽  
2021 ◽  
pp. 1-11
Author(s):  
Zhengshuai Wang ◽  
Chuanguang Zhu ◽  
Hongzhen Zhang ◽  
Jianrong Kang ◽  
Jinshan Hu
Keyword(s):  
Robust Estimation ◽  
Integral Method ◽  
Model Parameters ◽  
Probability Integral Method ◽  
Probability Integral ◽  
Estimation Of Model Parameters
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