A New Micro Magnetic Bridge Probe in Magnetic Flux Leakage for Detecting Micro-cracks

Li, Erlong; Kang, Yihua; Tang, Jian; Wu, Jianbo

doi:10.1007/s10921-018-0499-8

Cited by 31 publications

(11 citation statements)

References 20 publications

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“…J. Wu proposed to use a magnetic head (as shown in Figure 13 ) to detect tiny cracks in bearings [ 126 ], J. Tang further studied the influence of head pose on the MFL signal [ 127 ]. E. Li studied the relationship between the size of the opening in the magnetic head and the frequency of the MFL signal and designed a magnetic head structure for trans-scale defects [ 128 , 129 ]. S. Liu proposed a magnetic focusing sensor that adds a magnetic guide core and a permanent magnet to coils [ 130 ].…”

Section: Excitation and Sensing Techniques In Mfl Testingmentioning

confidence: 99%

A Review of Magnetic Flux Leakage Nondestructive Testing

Feng

et al. 2022

Materials

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Magnetic flux leakage (MFL) testing is a widely used nondestructive testing (NDT) method for the inspection of ferromagnetic materials. This review paper presents the basic principles of MFL testing and summarizes the recent advances in MFL. An analytical expression for the leakage magnetic field based on the 3D magnetic dipole model is provided. Based on the model, the effects of defect size, defect orientation, and liftoff distance have been analyzed. Other influencing factors, such as magnetization strength, testing speed, surface roughness, and stress, have also been introduced. As the most important steps of MFL, the excitation method (a permanent magnet, DC, AC, pulsed) and sensing methods (Hall element, GMR, TMR, etc.), have been introduced in detail. Finally, the algorithms for the quantification of defects and the applications of MFL have been introduced.

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Section: Excitation and Sensing Techniques In Mfl Testingmentioning

confidence: 99%

A Review of Magnetic Flux Leakage Nondestructive Testing

Feng

et al. 2022

Materials

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“…Experiment 2 investigates the effect of surface roughness on the reliability of wet MPI when detecting discontinuities. The drilled holes are expected to create MFL; if there is an adequate amount of MFL, particles will be pulled from the area surrounding the discontinuity which will alter the noise area percentage [11]. Hence, Experiment 2 was planned to investigate the influence of surface roughness on the noise area percentage when a discontinuity is present in the part.…”

Section: Fig 11 the Surface Classifications On The Samplesmentioning

confidence: 99%

Development of an Image Analysis Protocol to Define Noise in Wet Magnetic Particle Inspection

2021

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This study presents a novel method to quantify the effectiveness of wet magnetic particle inspection (MPI) when detecting possible defects. Wet MPI is an established method utilizing magnetic fields to locate possible areas of defects in ferromagnetic parts. The capability of this method has been evaluated in the past most notably using the probability of detection (POD) graphs. However, MPI requires a large amount of data and is subjective because it is based on human operators' evaluation. The method proposed in this paper is an objective method to determine the effectiveness of the MPI test based on how well discontinuities can be delineated in the image. This approach utilizes the intensity of the particle illumination in the defect area and compares it to its surroundings. This analysis generates a value to objectively represent how well a discontinuity can be identified. This method was then used to validate the effect of surface roughness on the effectiveness of wet MPI using two experiments. The first experiment was conducted to test for the collection of particles on varying surface roughness levels, and the second experiment was used to evaluate the effect of surface roughness when detecting a subsurface discontinuity. Results indicate that there is a significant increase in particle collection as roughness increases and as the surface roughness increases, the harder it is to locate discontinuities. This method provides a quantitative measure that could be used to aid parameter selection.

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“…Magnetic flux leakage (MFL) testing has been used as a high-speed and high-sensitivity non-destructive testing (NDT) method for decades [ 1 , 2 , 3 , 4 ]. The MFL testing has gained good performance in the detection of defects in ferromagnetic objects such as pipelines, wire ropes, tanks, etc.…”

Section: Introductionmentioning

confidence: 99%

Defect Width Assessment Based on the Near-Field Magnetic Flux Leakage Method

Chen

et al. 2021

Sensors

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Magnetic flux leakage (MFL) testing has been widely used as a non-destructive testing method for various materials. However, it is difficult to separate the influences of the defect geometrical parameters such as depth, width, and length on the received leakage signals. In this paper, a “near-field” MFL method is proposed to quantify defect widths. Both the finite element modelling (FEM) and experimental studies are carried out to investigate the performance of the proposed method. It is found that that the distance between two peaks of the “near-field” MFL is strongly related to the defect width and lift-off value, whereas it is slightly affected by the defect depth. Based on this phenomenon, a defect width assessment relying on the “near-field” MFL method is proposed. Results show that relative judging errors are less than 5%. In addition, the analytical expression of the “near-field” MFL is also developed.

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A New Micro Magnetic Bridge Probe in Magnetic Flux Leakage for Detecting Micro-cracks

Cited by 31 publications

References 20 publications

A Review of Magnetic Flux Leakage Nondestructive Testing

A Review of Magnetic Flux Leakage Nondestructive Testing

Development of an Image Analysis Protocol to Define Noise in Wet Magnetic Particle Inspection

Defect Width Assessment Based on the Near-Field Magnetic Flux Leakage Method

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