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The positioning of buried pipelines from magnetic data

摘要:Buried pipelines are "lifelines" for cities; therefore, it is vital to understand their location and depth before municipal construction to prevent them from being damaged. Magnetic methods have been applied to detect buried ferrous metal pipelines such as steel and cast-iron pipes. We have developed a positioning method for buried pipelines from magnetic data, which is based on a combination of the tilt angle and the downward continuation. The magnetic tilt angle can provide information about the location and depth of buried pipelines, which can easily be calculated by the horizontal and vertical magnetic field gradients. We prove that the tilt angle for the magnetic field that has been reduced to the pole is independent of the magnetization direction given by the pipeline direction with respect to the inducing field. A tilt angle of 90 degrees marks the location of a buried pipeline, whereas the depth is the distance between the location of the 90 degrees and its adjacent 0 degrees. The iterative Tikhonov regularization method for downward continuation, while separating the superimposed anomalies and enhancing the horizontal resolution, also reduces the influence of fast Fourier transform-induced noise and other noise that is intrinsic to the data set. We use the derivative of the Tikhonov regularization result as a regularization term of the minimization function and a constraint for the regularization parameter choice to obtain a more stable and accurate downward-continued result. This positioning method is applicable to single and parallel pipeline detection.

ISSN号:0016-8033

卷、期、页:卷: 85期: 6页: J111-J120

发表日期:2020-11-01

影响因子:2.792900

期刊分区(SCI为中科院分区):三区

收录情况:SCI(科学引文索引印刷版),地学领域高质量科技期刊分级目录(国外T1),EI(工程索引),SCIE(科学引文索引网络版)

发表期刊名称:GEOPHYSICS

通讯作者:李彩芳,孟晋,刘家琳,张妍

第一作者:刘得军

论文类型:期刊论文

论文概要:李彩芳,刘得军,孟晋,刘家琳,张妍,The positioning of buried pipelines from magnetic data,GEOPHYSICS,2020,卷: 85期: 6页: J111-J120

论文题目:The positioning of buried pipelines from magnetic data

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