Quantitative study on the propagation characteristics of MMM signal for stress internal detection of long distance oil and gas pipeline

Liu, Bin; Ma, Zeyu; He, Limin; Wang, Di; Zhang, Hai; Ren, Jinchang

doi:10.1016/j.ndteint.2018.08.006

Cited by 26 publications

(9 citation statements)

References 21 publications

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“…The slope of the fitted curve for the radial component change is greater than the slope of the fitted curve for the axial component at the time of the change in the lift-off value, and the radial component change is more pronounced. The experimental results of magnetic signal acquisition with different lift-off values show a consistent trend with the experimental results in [38,39], which verifies the correctness of the theoretical model.…”

Section: Spatial Distribution Of the Leakage Signal For Different Val...supporting

confidence: 84%

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: Spatial Distribution Of the Leakage Signal For Different Val...supporting

confidence: 84%

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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“…At the notch, Hx mutated and presented in a "trough" shape, Hy remained almost constant and rotated around the midpoint, and the slope of At the stage of fatigue crack propagation, as shown in Figure 10f,h, there were numerous dislocations stacking in the plastic deformation regions, which were located on both sides of the crack, so the dislocation density at the notch was larger than other regions. According to the theory of magnetic charge [22,23], magnetic domain walls are mainly fixed in dislocations and the dislocations will lead to the accumulation of magnetic charges in the plastic deformation zone, this can be seen in Figure 10e,g. With the fatigue crack propagation, more and more magnetic charges were accumulated at the root of the notch and on both sides of the fatigue crack.…”

Section: Discussionmentioning

confidence: 98%

Variation of Magnetic Memory Signals in Fatigue Crack Initiation and Propagation Behavior

Zhou

Fan

et al. 2019

Metals

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To monitor fatigue crack initiation and propagation, and to judge the fatigue damage status of ferromagnetic material, fatigue bending tests of four-point single edge notch bend (SENB4) specimens were carried out. Metal magnetic memory signals were measured during the whole fatigue process. The results showed that the fatigue process could be divided into four stages by observing the morphology of the fracture surface. With the increase of fatigue loading cycles, the tangential component of the magnetic field (Hx) and the normal component of the magnetic field (Hy) increased. At the notch Hx presented a “trough” shape and had a maximum value at the midpoint, while Hy at the notch rotated clockwise around the midpoint. Compared with the tangential characteristic parameters, the variation of normal characteristic parameters (i.e., maximum gradient value of Hy (Ky-max) and the variation range of Hy at the notch (∆Hyn), with the fatigue loading cycles are more similar to the variation of fatigue crack length with loading cycles), both Ky-max and ∆Hyn had a good linear relationship with fatigue crack length. Plastic deformation accumulated on both sides of the fatigue crack, and metal magnetic memory (MMM) signals measured from the specimens were able to indicate the location of the fatigue crack and the variation of the fatigue crack length. Furthermore, the distribution of magnetic signals was analyzed according to the theories of stress magnetization and magnetic flux leakage.

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“…According to the non-uniform magnetic charge model under stress, this study presented a method to quantify the MFL signals of defects [ 38 , 39 ].…”

Section: Model Developmentmentioning

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 the propagation characteristics of MMM signal for stress internal detection of long distance oil and gas pipeline

Cited by 26 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

Variation of Magnetic Memory Signals in Fatigue Crack Initiation and Propagation Behavior

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

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