Quantitative Study on MFL Signal of Pipeline Composite Defect Based on Improved Magnetic Charge Model

Liu, Bin; Luo, Ning; Gang, Feng

doi:10.3390/s21103412

Cited by 18 publications

(8 citation statements)

References 21 publications

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“…Half of the magnetic charge distributed on the defect is positive and the other half is negative, and the axes of coordinates x, y, z are established along the three orthogonal directions of the cylindrical slot, and the length, width, and depth of the defect are 2D x , 2D z and D y respectively. Assuming that the external magnetic field H is along the X-axis direction, the coordinates of the three-dimensional spatial field point are defined as P(x, y, z), and the coordinates of the source point of the magnetic charge surface are M(x m , y m , z m ), the magnetic field intensity generated by the microfacet element dy m dz m on the magnetic charge surface at point P can be expressed as [26][27][28]:…”

Section: Model Constructionmentioning

confidence: 99%

Study of MFL signal identification in pipelines based on non-uniform magnetic charge distribution patterns

Liu¹,

Lian²,

Liu³

et al. 2023

Meas. Sci. Technol.

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Magnetic flux leakage (MFL), a pipeline internal detection, is the mainstream technology for international oil and gas pipeline safety maintenance. To address the problem of large errors in the assessment of defects in pipeline inspection by existing theoretical analysis models, this paper introduces the charge density parameter to establish a mathematical model of non-uniform magnetic charge for pipeline leakage detection and calculates the non-uniform distribution pattern of magnetic charge on the defect side wall. The contour plot method is proposed to visually analyze the size of defects. To compare the error between uniform and non-uniform models, and verify the correctness of the theoretical model, experiments were systematically conducted on the X70 pipeline with internal MFL technology. The results show that: the magnetic charge distribution curve is symmetrically shaped at the center of the defect, with a valley at the center and two peaks at the defect edge. As the defect depth and width increase, the magnetic charge density increases sharply near the surface and edge. The peak-to-valley spacing and peak-to-valley values in the contour map of the magnetic flux leakage signal can directly reflect the location and size of defects. The signal characteristic values follow the trend of a first-order decreasing exponential function as the value of the lift-off increases. The first-order derivative of the signal characteristic value tends to decrease and then increase as the mesh size decreases, and the extreme point of the derivative curve is the best mesh size.

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Section: Model Constructionmentioning

confidence: 99%

Study of MFL signal identification in pipelines based on non-uniform magnetic charge distribution patterns

Liu¹,

Lian²,

Liu³

et al. 2023

Meas. Sci. Technol.

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“…In the current research, the common electromagnetic nondestructive evaluation methods for defect size evaluation include eddy current testing (ECT) [ 4 , 5 , 6 , 7 ], pulsed eddy current testing (PECT) [ 8 , 9 , 10 , 11 , 12 ], and magnetic flux leakage (MFL) testing [ 13 , 14 , 15 ], alternating current field measurement (ACFM) [ 16 , 17 , 18 ]. MFL [ 19 , 20 , 21 , 22 , 23 ] was limited by wall thickness, while the signal for evaluating defects in thick-walled components is attenuated with increasing wall thickness, and some of them [ 24 , 25 , 26 , 27 , 28 , 29 , 30 ] were often affected by skin effects or magnetic shielding effects. Nowadays, some scholars [ 31 , 32 , 33 , 34 ] evaluated defects through signal characterization with algorithmic optimization.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Depth Size Based on Layered Magnetization by Double-Sided Scanning for Internal Defects

Deng,

Qian,

Hong

et al. 2024

Sensors

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The quantitative evaluation of defects is extremely important, as it can avoid harm caused by underevaluation or losses caused by overestimation, especially for internal defects. The magnetic permeability perturbation testing (MPPT) method performs well for thick-walled steel pipes, but the burial depth of the defect is difficult to access directly from a single time-domain signal, which is not conducive to the evaluation of defects. In this paper, the phenomenon of layering of magnetization that occurs in ferromagnetic materials under an unsaturated magnetizing field is described. Different magnetization depths are achieved by applying step magnetization. The relationship curves between the magnetization characteristic currents and the magnetization depths are established by finite element simulations. The spatial properties of each layering can be detected by different magnetization layering. The upper and back boundaries of the defect are then localized by a double-sided scan to finally arrive at the depth size of the defect. Defects with depth size of 2 mm are evaluated experimentally. The maximum relative error is 5%.

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“…The quantization of the pipeline MFL signal is the ultimate goal of MFL detection [ 14 ]. Most of the quantization methods are to carry out a large number of calibrations of experimental data [ 15 , 16 ], but the failure to take into account the complex situation in the pipeline will lead to poor accuracy and impracticality of the quantization method; therefore, the quantization of the theoretical model has become a hot research topic [ 17 , 18 ]. Under the influence of the internal pressure of the medium and the surrounding environment, there is a large stress concentration area at the defect [ 19 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

The Signal Characteristics of Oil and Gas Pipeline Leakage Detection Based on Magneto-Mechanical Effects

Liu

et al. 2023

Sensors

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In order to solve the problem of the quantification of detection signals in the magnetic flux leakage (MFL) of defective in-service oil and gas pipelines, a non-uniform magnetic charge model was established based on magnetic effects. The distribution patterns of magnetic charges under different stresses were analyzed. The influences of the elastic load and plastic deformation on the characteristic values of MFL signals were quantitatively assessed. The experimental results showed that the magnetic charge density was large at the edges of the defect and small at the center, and approximately decreased linearly with increasing stress. The eigenvalues of the axial and radial components of the MFL signals were compared, and it was found that the eigenvalues of the radial component exhibited a larger decline rate and were more sensitive to stress. With the increase in the plastic deformation, the characteristic values of the MFL signals initially decreased and then increased, and there was an inflection point. The location of the inflection point was associated with the magnetostriction coefficient. Compared with the uniform magnetic charge model, the accuracy of the axial and radial components of the MFL signals in the elastic stage of the improved magnetic charge model rose by 17% and 16%, respectively. The accuracy of the axial and radial components of the MFL signals were elevated by 9.15% and 9%, respectively, in the plastic stage.

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Quantitative Study on MFL Signal of Pipeline Composite Defect Based on Improved Magnetic Charge Model

Cited by 18 publications

References 21 publications

Study of MFL signal identification in pipelines based on non-uniform magnetic charge distribution patterns

Study of MFL signal identification in pipelines based on non-uniform magnetic charge distribution patterns

Evaluation of Depth Size Based on Layered Magnetization by Double-Sided Scanning for Internal Defects

The Signal Characteristics of Oil and Gas Pipeline Leakage Detection Based on Magneto-Mechanical Effects

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