Location and depth estimation of point-dipole and line of dipoles using analytic signals of the magnetic gradient tensor and magnitude of vector components

Oruç, Bülent

doi:10.1016/j.jappgeo.2009.10.002

Cited by 49 publications

(17 citation statements)

References 22 publications

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“…the left is negative and the right is positive. There are also two kinds of triple anomaly: central positive anomaly, and central negative anomaly (Furness, 2007;Oruç, 2010;Sanchez et al, 2008). An anomaly area of each type can be characterized by its amplitude and width (Shaw et al, 2007).…”

Section: Model Representationmentioning

confidence: 99%

“…Depth has an obvious effect on the magnetic anomaly curve (Ma and Li, 2013;Oruç, 2010;Shaw et al, 2007). Depth is first estimated by the shape and amplitude of magnetic anomaly curve when analyzing the effect of depth on magnetic anomaly, thus providing an initial value for further calculation to determine an accurate depth.…”

Section: Influence Of Pipeline Spatial Positionmentioning

confidence: 99%

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Forward modeling of total magnetic anomaly over a pseudo-2D underground ferromagnetic pipeline

Guo

Liu

Pan

et al. 2015

Journal of Applied Geophysics

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Section: Model Representationmentioning

confidence: 99%

Section: Influence Of Pipeline Spatial Positionmentioning

confidence: 99%

Forward modeling of total magnetic anomaly over a pseudo-2D underground ferromagnetic pipeline

Guo

Liu

Pan

et al. 2015

Journal of Applied Geophysics

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“…HE precise measurement of Earth's magnetic field plays important role in geophysics, astrospace magnetic measurement, Manuscript mine detection and national defense [1][2][3]. Since the magnetic field is a vector field, there are four different types of measurements that can be made during surveying: the total magnetic intensity (TMI); the components of the vector field; the gradient of the total field; and the gradient tensor of the vector field.…”

Section: Introductionmentioning

confidence: 99%

Two-Step Complete Calibration of Magnetic Vector Gradiometer Based on Functional Link Artificial Neural Network and Least Squares

Huang

2016

IEEE Sensors J.

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Magnetic vector gradiometers are frequently used for the detection of ferrous metals, the detection of unexploded ordinance (UXO) and defense applications. A magnetic vector gradiometer, which is under consideration in this paper, consists of two tri-axial magnetometers (TAMs). It requires a calibration procedure in order to take into account the errors in the TAM(tri-axial magnetometer) itself and the spatial misalignment of the magnetometers that will deteriorate the measurement precision of the gradiometer. This paper reports a two-step calibration algorithm of magnetic vector gradiometer based on functional link artificial neural network (FLANN) and least squares according to its response to an external magnetic vector field. The procedure and steps to identify the coefficients related to the measurement error are given. The calibration algorithm with good convergence proved by the numerical simulations decreased the relative error of magnetic vector gradient, in the case when the TAM is used in earth field, from 6.2340 down to 0.0187 and the parameters can be identified with the maximum inaccuracy of 5.35%. The efficiency of two-step calibration is also validated through experimental tests of two TAMs of type Mag03-MSB100 strapped on a nonmagnetic turntable. The calibrated coefficients are a good match with those specified by the manufacturer of the TAMs; the standard deviations of the increments of magnetic vector components in x, y and z directions decrease from 74.655nT, 90.617nT and 162.39nT before calibration down to 18.793nT, 20.095nT and 13.671nT after calibration, respectively.

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“…Some people (Beiki and Pedersen, 2010;Beiki et al, 2011;Wu et al, 2011) presented using the eigenvector of tensor gradient data to ascertain the locations of the geological bodies. Oruç (2010aOruç ( , 2010b combined the gravity tensor gradient invariants and vertical component to estimate the source depth. Oruç (2010aOruç ( , 2010b used the analytic signals of the magnetic tensor gradient and magnitude of vector components to compute the locations of the dipoles.…”

Section: Introductionmentioning

confidence: 99%

“…Oruç (2010aOruç ( , 2010b combined the gravity tensor gradient invariants and vertical component to estimate the source depth. Oruç (2010aOruç ( , 2010b used the analytic signals of the magnetic tensor gradient and magnitude of vector components to compute the locations of the dipoles. Ma et al (2012) presented tensor local wavenumber method interpret the tensor gradient data.…”

Section: Introductionmentioning

confidence: 99%

Balanced gradient methods for the interpretation of gravity tensor gradient data

Lu¹,

2015

Journal of Applied Geophysics

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Location and depth estimation of point-dipole and line of dipoles using analytic signals of the magnetic gradient tensor and magnitude of vector components

Cited by 49 publications

References 22 publications

Forward modeling of total magnetic anomaly over a pseudo-2D underground ferromagnetic pipeline

Forward modeling of total magnetic anomaly over a pseudo-2D underground ferromagnetic pipeline

Two-Step Complete Calibration of Magnetic Vector Gradiometer Based on Functional Link Artificial Neural Network and Least Squares

Balanced gradient methods for the interpretation of gravity tensor gradient data

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