Enhanced Detection of Defects Using GMR Sensor Based Remote Field Eddy Current Technique

Park, J. W.; Park, J. H.; Song, Sung‐Jin; Kishore, M. B.; Kwon, Segon; Kim, H. J.

doi:10.4283/jmag.2017.22.4.531

Cited by 10 publications

(5 citation statements)

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“…The flux leakage is detected with the help of Hall, coil, and magnetoresistance (MR) sensors, respectively [20][21][22]. From the group of MR sensors, giant magnetoresistance (GMR) has gained many advantages over the other sensors in terms of sensitivity, compactness, and cost [23][24][25]. In general, the pipeline inspection robot needs a constant driving force to move from one end to another while inspecting the pipes.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Leakage in a Sustainable Water Pipeline Based on a Magnetic Flux Leakage Technique

et al. 2022

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Pipelines are typically used to transport oil, natural gas, water, etc. It is one of the most effective methods for transferring fluids over long distances. However, long-term usage of these pipes without maintenance results in the formation of residues, which will pave the way for pipeline accidents and soil contamination. To ensure the safety and protection of resources, these sustainable pipelines need to be inspected to avoid losses. This work aims to investigate various internal defect leaks in the non-uniform thickness of sustainable water pipes that are joined with a pipe expander. The magnetic flux leakage technique was implemented to evaluate these defects by means of a flexible GMR sensor array. An inspection robot containing two units was fabricated with the aid of 3D printing. The power unit provides the necessary thrust to actuate the entire robot whereas the sensing unit is responsible for analyzing the leaks. The robot’s movement is predicted by the MPU6050 and ultrasonic distance sensors that are plotted as motion plots. The sensing unit consists of permanent magnets and a giant magnetoresistance (GMR) array to interrogate the flux leakage in the defect region. The flux leakage from the defects was stored with the help of an Arduino microcontroller, which controls the overall process. In addition, the spring suspension is provided to regulate the motion of the robot. The flux leakage from the defect region was plotted as waveform graphs. Thus, the results are effectively presented and compared. The calculated signal-to-noise ratio (SNR) of the magnetic flux leakages (MFLs) for 4.5 mm-thick pipe defects was 12 to 20.8 dB, and for 6.52 mm-thick pipe defects, it was 9.5 to 19 dB. In sum, the MFL technique provides a reliable method for the sustainable development of water supply to wide areas.

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Section: Introductionmentioning

confidence: 99%

Analysis of Leakage in a Sustainable Water Pipeline Based on a Magnetic Flux Leakage Technique

et al. 2022

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“…Therefore, eddy current inspection can be used to inspect the inside of the rail, which gives it an advantage over visual inspection, and it can be used very usefully because it can inspect the surface area, which gives it an advantage over ultrasonic inspection [7,8]. In the eddy current inspection method, a Lissajous figure can be drawn using X data (resistance) and Y data (reactance), which are signal outputs from the sensor, and the size of a defect can be obtained using amplitude and phase [9,10].…”

Section: Introductionmentioning

confidence: 99%

Natural Rail Surface Defect Inspection and Analysis Using 16-Channel Eddy Current System

Kwon¹,

Lee²,

Park³

et al. 2021

Applied Sciences

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Trains are used as the fastest mode of transportation for both people and cargo. The train moves along a special path called 'rail,' where fatigue can be accumulated due to wheel-rail contact load as a result of continuous train operation. Consistent and regularly scheduled safety management is required since corrosion rate of the rails located on outside environment is very high. Researchers have actively investigated and developed rail defect inspection systems employing non-destructive techniques to address these problems. In particular, the eddy current inspection technique does not involve contact with the surface of the test specimen and offers the advantage of excellent rail defect detection sensitivity. Therefore, a 16 Ch array eddy current inspection device was developed to inspect the surface defects of the rail. An equation was derived to predict the correlation between the depth and phase of an artificial defect using the eddy current inspection device, and the derived equation was applied to the natural defect specimen.

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“…In ECT, alternating current is applied to a coil sensor to produce a magnetic field, which produces an eddy current due to electromagnetic induction as the surface of the test specimen is approached [8,9]. The eddy current distributed on the test specimen surface is established in the opposite direction of the magnetic field produced by the coil sensor, and thus when defects or nonuniform areas exist, the difference in the magnetic fields produced by the coil and the test surface results in variations in the impedance and electromotive force [10][11][12]. Therefore, information on defects such whether defects exist and their sizes and depths can be obtained through the electrical signal variation such as the impedance between the test surface and the coil sensor [13,14].…”

Section: Introductionmentioning

confidence: 99%

Rail Surface Defect Detection and Analysis Using Multi-Channel Eddy Current Method Based Algorithm for Defect Evaluation

Park

Lee²,

Back

et al. 2021

J Nondestruct Eval

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The railroad rail support trains and contributes to their operation. Internal and surface defects occur on the rail due to various combinations of causes including fatigue loading and cyclic tension and compression among others from the deterioration of the rail along with the temperature differences of seasonal changes. Surface defects such as head check, shelling, and squats start out in the rail head and become internal defects due to poor maintenance, ultimately resulting in rail failure. In order to prevent rail failure, it is important that defects are identified through nondestructive evaluation (NDE) in advance and to carry out maintenance techniques including grinding. NDE methods include MFL, EMAT, and ECT, and among these, the ECT method is a representative method with excellent detection sensitivity that nondestructively inspects metal surfaces such as rails and pipes using an electromagnetic field. Also, since the defect signal is obtained as an electrical signal, the depth, length, and width of defects can be assessed using a defect evaluation algorithm. This study investigated the field applicability and future practical use of the 16 channel eddy current testing equipment and defect evaluation algorithm developed in this study. Therefore, the field applicability of the equipment and defect evaluation algorithm was investigated through the detection of artificial defects with varying size and depth. Afterwards, future practical use was evaluated by inspection of areas of rail that are in use and with naturally occurring surface defects and analysis of their size (length, width), depth, and phenomena.

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Enhanced Detection of Defects Using GMR Sensor Based Remote Field Eddy Current Technique

Cited by 10 publications

References 0 publications

Analysis of Leakage in a Sustainable Water Pipeline Based on a Magnetic Flux Leakage Technique

Analysis of Leakage in a Sustainable Water Pipeline Based on a Magnetic Flux Leakage Technique

Natural Rail Surface Defect Inspection and Analysis Using 16-Channel Eddy Current System

Rail Surface Defect Detection and Analysis Using Multi-Channel Eddy Current Method Based Algorithm for Defect Evaluation

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