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Prediction of 3D deformation due to large gradient mining subsidence based on InSAR and constraints of IDPIM model

机译:基于IDPIM模型的insar和约束的大梯度矿区3D变形预测

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摘要

After underground coal resources are mined out in mining areas, large-gradient deformation is prone to occur on the ground surface during a short period of time. When the deformation gradient exceeds the threshold value of the gradient monitored by the D-InSAR (Differential Interferometry Synthetic Aperture Radar) technology, the conventional D-InSAR technology is likely to cause the failure of InSAR (Interferometry Synthetic Aperture Radar) phase unwrapping algorithms. In this case, neither the conventional D-InSAR technology nor the method of prior model + InSAR can obtain the 3D (three-dimensional) deformation field of mining-induced subsidence. Aiming at these problems, a method of monitoring 3D deformation of mining subsidence with large gradient was developed in this paper, which combines the improved dynamic prediction model and a single pair of D-InSAR. The probability integral method was firstly improved, and its problem of fast convergence at the edge of the subsidence basin was solved. Secondly, according to the geometric projection relationship between the LOS (Light Of Sight) deformation of D-InSAR in the mining area and the 3D surface deformation, the observation condition equation of the mining subsidence monitored by D-InSAR based on the improved dynamic model of PIM (Probability Integral Method) was established. Then, the solving model of prediction parameters of the improved dynamic model of PIM was constructed according to the GA (Genetic Algorithm) theory. Finally, based on the LOS deformation obtained by D-InSAR technology, the 3D deformation of mining subsidence is obtained by the 3D deformation predicting method proposed in this paper. The feasibility of the method was verified by the simulation experiment results. The LOS deformation at the edge of the subsidence basin was obtained by the differential interference processing of data from two images of Sentinel-1A on 16 November 2017 and 10 December 2017 of 1613 working face of Guqiao South Mine. The 3D deformation of the surface in the mining area during this period were obtained by using the method proposed in this paper. The predicted subsidence value was compared with the measured surface subsidence value. The result is as follow: the maximum error value of subsidence was 60 mm, about 9.1% of the maximum value of subsidence, and the fitting error of mean square of subsidence was +/- 26.21 mm. The results show that the predicting 3D deformation method of D-InSAR for large gradient of mining subsidence based on constraints of improved dynamic prediction model proposed in this paper has certain engineering application values.
机译:在矿区挖掘地下煤炭资源之后,在短时间内,在地面上易于发生大渐变变形。当变形梯度超过由D-Insar(差分干涉式合成孔径雷达)技术监测的梯度的阈值时,传统的D-INSAR技术可能导致INSAR(干涉学合成孔径雷达)相位展开算法的故障。在这种情况下,传统的D-INSAR技术和现有模型+ INSAR的方法都无法获得采矿诱导沉降的3D(三维)变形领域。针对这些问题,在本文中开发了一种监测具有大梯度的挖掘沉降的3D变形的方法,其结合了改进的动态预测模型和一对D-Insar。首先改善了概率积分方法,解决了沉降盆地边缘的快速收敛问题。其次,根据矿区D-Insar的LOS(视光)之间的几何投影关系和3D表面变形,基于改进动态模型的D-Insar监测挖掘沉降的观察条件方程建立了PIM(概率积分法)。然后,根据GA(遗传算法)理论构建了PIM改进动态模型的求解参数的求解参数。最后,基于通过D-Insar技术获得的LOS变形,通过本文提出的3D变形预测方法获得挖掘沉降的3D变形。通过模拟实验结果验证了该方法的可行性。沉降盆地边缘的LOS变形是通过来自2017年11月16日的Sentinel-1a图像的数据的差异干扰处理和2017年12月10日的Guqiao South Lime 1613年12月10日。通过使用本文提出的方法,获得在此期间在该时间段内的表面的3D变形。将预测的沉降值与测量的表面沉降值进行比较。结果如下:沉降的最大误差值为60毫米,沉降的最大值的约9.1%,沉降的均线误差为+/- 26.21 mm。结果表明,基于本文提出的改进的动态预测模型的约束,对大型挖掘的D-Insar的预测3D变形方法具有一定的工程应用值。

著录项

  • 来源
    《International journal of remote sensing》 |2021年第2期|208-239|共32页
  • 作者单位

    Anhui Univ Sci & Technol Sch Earth & Environm Huainan 232001 Peoples R China;

    Anhui Univ Sci & Technol Sch Geodesy & Geomat Huainan 232001 Peoples R China;

    Anhui Univ Sci & Technol Sch Geodesy & Geomat Huainan 232001 Peoples R China;

    China Univ Min & Technol Sch Environm Sci & Spatial Informat Xuzhou Peoples R China;

    Anhui Univ Sci & Technol Sch Earth & Environm Huainan 232001 Peoples R China;

    Anhui Univ Sci & Technol Sch Geodesy & Geomat Huainan 232001 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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