• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.6
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• pp.521-526
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• 2010

Gas transmission pipelines are often inspected and monitored using the magnetic flux leakage method. An inspection vehicle known as a "pig" is launched into the pipeline and conveyed along the pipe by the pressure of natural gas. The pig contains a magnetizer, an array of sensors and a microprocessor-based data acquisition system for logging data. This paper describes magnetic flux leakage (MFL) signal processing used for detecting mechanical damages during an in-line inspection. The overall approach employs noise removal and clustering technique. The proposed method is computationally efficient and can easily be implemented. Results are presented and verified by field tests from an application of the signal processing.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.402-402
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• 2000

MFL(Magnetic Flux Leakage) methods are used extensively for inspection of ferromagnetic materials. As an example, pipelines that are buried underground are inspected using MFL methods. By the MFL methods, ferromagnetic pipelines are magnetized by a permanent magnet or an electromagnet and then flux leakage is detected at the defection position. In this paper, we perform modeling of the magnetized pipelines. Also we propose the method localization of th defected areas. The effectiveness of the proposed method is verified experimentally.

• Journal of the Korean Magnetics Society
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• v.23 no.1
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• pp.18-25
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• 2013

MFL PIG (Magnetic Flux Leakage Pipeline Inspection Gauge) is called the system which detects the defect for underground pipelines by using magnetic flux leakage method in nondestructive testing. This method is very suitable for testing pipelines because pipeline has high magnetic permeability. MFL PIG generates the magnetic fields to the pipe axially oriented, and detect the signal of leakage flux by using hall sensor. However, MFL PIG is hard to detect the axially oriented crack with small size because the magnetic flux leakage is not enough to be occurred. To detect the small size and axially oriented crack, the circumferential MFL (CMFL) PIG is being proposed and it can maximize the leakage flux for the axial crack by performing magnetic fields circumferentially on the pipe. In this paper, CMFL PIG is applied to detect the axially oriented crack with small size and the analysis for the distribution and the amplitude of the leakage flux signal is performed by using three dimensional finite element method. From sensing signals, the method how to determine the shape of axially oriented cracks is proposed and verified with experiment.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.7
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• pp.129-136
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• 2019

In this study, the magnetic flux leakage technique was applied to diagnose steel plate damage, imaging technique was applied through those signals. Steel plate specimens with different thicknesses were prepared for the imaging the magnetic flux leakage signal, and 6 different depths of damage were artificially processed at the same locations on each specimen. The sensor head consist hall sensor and magnetization yoke was fabricated to magnetize the steel plate specimen and measure the magnetic flux leakage signal. In order to remove the noise and increase the resolution of the image in the signal collected from the hall sensor, various of signal processing was performed. P-P value was analyzed for each channel to analyze the magnetic flux leakage signals measured from each damaged part. Based on the above processed signals and analysis, it was converted into heatmap image. Through this, it was possible to identify the damage on the steel plate at glance by imaging magnetic flux leakage signal.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.79.5-79
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• 2002

$\textbullet$ Introduction $\textbullet$ Deterioration of wire rope $\textbullet$ Magnetic flux leakage Instrument $\textbullet$ Experiment setup $\textbullet$ Performance of the instrument $\textbullet$ Conclusions

• Journal of Magnetics
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• v.15 no.4
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• pp.199-203
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• 2010

This paper discusses the effectiveness of high magnetization saturation in ILI (In-Line Inspection) using an MFL (Magnetic Flux Leakage) tool, and introduces a practical method for improving the magnetization level together with the piggability. Thin steel plates, replacing the conventional wire brushes were used as conductors to transfer the magnetic flux to the pipe wall. The newly designed MFL tool was compared with the conventional version by means of FEM (Finite Element Method) analysis and full-scale experiments. In the results, the newly developed magnetization system obtained a stronger MFL signal amplitude, specially 2.7 times stronger, than that obtained by the conventional magnetization system for the same defect dimensions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.5
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• pp.876-883
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• 2007

The magnetic flux leakage(MFL) type nondestructive testing(NDT) method is widely used to detect corrosion, defects and mechanical deformation of the underground gas pipelines. The object pipeline is magnetically saturated by the magnetic system with permanent magnet and yokes. Hall sensors detect the leakage fields in the region of the defect. The defects are sometimes occurred in group. The accuracy of the detecting signals in this defect cluster become lowered because of the complexity of the defect cluster. In this paper, the effects of the multi -defects are analyzed. The detecting signals are computed by 3-dimensional finite element method and compared with real measurement. The results say that, rather than the size of the defects, the effects of the relative position of the multi-defects are very important on the detecting signals.

• Journal of Sensor Science and Technology
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• v.15 no.5
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• pp.328-333
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• 2006

Magnetic Flux Leakage (MFL) methods are widely employed for the nondestructive evaluation (NDE) of gas pipelines. In the application of MFL pipeline inspection technology, corrosion anomalies are detected and identified via their leakage filed due to changes in wall thickness. The gas industry is keenly interested in automating the interpretation process, because a large amount of data to be analyzed is generated for in-line inspection. This paper presents a novel approach to the tasks of data segmentation, feature extraction and depth estimation from gas pipelines. Also, we will show that the proposed method successfully identifying artificial defects.

• Journal of Mechanical Science and Technology
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• v.14 no.10
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• pp.1072-1080
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• 2000

Leakage magnetic flux (LMF) is widely used for non-contact detection of cracks. The combination of optics and LMF offers advantages such as real time inspection, elimination of electrical noise, high spatial resolution, etc. This paper describes a new nondestructive evaluation method based on an original magneto-optical inspection system, which uses a magneto-optical sensor, LMF, and an improved magnetization method. The improved magnetization method has the following characteristics: high observation sensitivity, independence of the crack orientation, and precise transcription of the geometry of a complex crack. The use of vertical magnetization enables the visualization of the length and width of a crack. The inspection system provides the images of the crack, and shows a possibility for the computation of its depth.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.4
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• pp.417-423
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• 2015

In this study, Magnetic Flux Leakage(MFL)-based inspection system was applied to detect the local fault of wire rope. To verify the feasibility of the proposed damage detection technique, an 4-channel MFL sensor head prototype was designed and fabricated. A wire rope with several types of cross-sectional damages were fabricated and scanned by the MFL sensor head to measure the magnetic flux density of the wire rope specimen. To interpret the condition of the wire rope, magnetic flux signals were used to determine the locations of the flaws. To improve the resolution of signal, the instantaneous variation value of magnetic flux was utilized. Measured signals from the damaged specimen were compared with thresholds set for objective decision making. Finally, the results were compared with information on actual inflicted damages to confirm the accuracy and effectiveness of the proposed cable monitoring method.