A Study of Leakage Magnetic Flux Detector Using Hall Sensors Array

Lee, Jin Yi; Hwang, Ji Seoung; Lee, Kyung Chul; Choi, Se Ho

doi:10.4028/www.scientific.net/kem.306-308.235

Cited by 23 publications

(10 citation statements)

References 2 publications

(3 reference statements)

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“…Correspondingly, the numerically analyzed MO sensor results have to be expressed by three color tones, bright for H Z >H S , dark for H Z <-H S and dusky for -H S <H Z <H S . On the other hand, the LMF density (B) and its processed results, such as the differential to the X direction (hereafter ∂B/∂x) and the differential to the Y direction (∂B/∂y), can be used by the Hall sensor for quantitative nondestructive evaluation of the crack in the LMF measurement system, such as a magnetic camera [5][6][7].…”

Section: Numerical Analysis Software Algorithm Using the Magnetic Dip...mentioning

confidence: 99%

Development of Numerical Analysis Software for the NDE by Using Dipole Model

Lee

Jun

Hwang

et al. 2007

KEM

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The magnetic field distribution around a crack can be calculated more easily and quickly by using a dipole model than finite element method (FEM). This paper reports the development of numerical analysis software that uses an improved dipole model to analyze the magnetic field around cracks. The preprocessor in this software includes the crack formation software, which can distribute the magnetic charge per unit area, m, on the crack section area. Also the lift-off, measurement area and sensor interval, and magnetization direction can be considered in the preprocessor. Also, the postprocessor presents functions, such as the natural magnetic field distribution and ∂B/∂x, ∂B/∂y, as results. Also, the physical characteristics of the magnetic optical sensor and the Hall sensor are included in the postprocessor, and the magnetic field distribution can be changed to optical intensity and electrical signal distribution. The experiment results, which are obtained by using the magnetic camera on the crack, are compared with analysis results obtained by using the dipole model analysis software.

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Section: Numerical Analysis Software Algorithm Using the Magnetic Dip...mentioning

confidence: 99%

Development of Numerical Analysis Software for the NDE by Using Dipole Model

Lee

Jun

Hwang

et al. 2007

KEM

Self Cite

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“…In magnetic flux leakage (MFL) inspection, the tested ferromagnetic specimen should be magnetized. At the region where a metal loss exists, the magnetic field would leak from the specimen into the surrounding air, and the leakage magnetic field can be measured by a magnetic sensor such as induction coils [10], Hall sensor [11] and TMR sensor [12]. The spatial distribution of the leakage magnetic field is related to the 3D shape of the defect.…”

Section: Introductionmentioning

confidence: 99%

Accurate 3D reconstruction of complex defects based on combined method of MFL and MFDs

Li¹,

Liu²,

Wu³

et al. 2021

Meas. Sci. Technol.

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The two-step strategy for 3D reconstruction of complex defects was updated by combining the magnetic field disturbance (MFD) with magnetic ﬂux leakage (MFL) measurement methods. Firstly, the plane-scanned MFD imaging was employed to achieve high-accuracy reconstruction of the opening outlines of complex defects. Secondly, the finite element simulation model of the defect with the recognized opening outline was established as the forward model for depth profile inversion with the particle swarm optimization algorithm. The performances of the conventional MFL-based and updated strategies were carefully compared through finite element simulation. The results proved that the updated method combining MFD signals with MFL signals had the better performance in accurate 3D reconstruction of complex defects than the conventional MFL-based inversion strategy, displaying smaller errors in opening outline, peak depth and the profile. Experimental results confirmed that the updated strategy could accurately reconstruct the 3D shape of 8-shaped defect and rectangular defect with rounded corners.

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“…Firstly, the location of a defect in the structure is important, with increased positional uncertainty leading to increased error in detection of defect locations. Secondly and more importantly, is that many NDE modalities require a carefully controlled stand-off distance from the surface for accurate defect detection and sizing [11][12][13]. A further challenge of NDE based localisation is that the typical environments into which platforms are deployed differ substantially, in terms of core materials and surfaces, to those discussed in localisation literature [14].…”

Section: Introductionmentioning

confidence: 99%