• Journal of Magnetics
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• v.18 no.3
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• pp.357-360
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• 2013

A modified SQI method using magnetic leakage flux (MFL) signal for underground gas pipelines' defect detection and characterization is presented in this paper. Raw signals gathered using MFL signals include many unexpected noises and high frequency signals, uneven background signals, signals caused by real defects, etc. The MFL signals of defect free pipelines primarily consist of two kinds of signals, uneven low frequency signals and uncertain high frequency noises. Leakage flux signals caused by defects are added to the case of pipelines having defects. Even though the SQI (Self Quotient Image) is a useful tool to gradually remove the varying backgrounds as well as to characterize the defects, it uses the division and floating point operations. A modified SQI having low computational complexity without time-consuming division operations is presented in this paper. By using defects carved in real pipelines in the pipeline simulation facility (PSF) and real MFL data, the performance of the proposed method is compared with that of the original SQI.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.4
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• pp.47-52
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• 2010

This paper describes a visualization technique that animates geometrical defect data that are extracted using a magnetic flux leakage (MFL) operating system on nondestructive evaluation (NDE). Since data are collected from different locations and often not regular, the data must be converted to the standard format that is used within the pipeline in visualization procedures. In order to navigate inside of the pipeline, 3D virtual objects are generated and are able to explore the pipeline continuously. The major objectives of this paper are to characterize, generate general shape of defects, and enable computer interaction in virtual environment. Pipeline navigation system (PNS) has introduced the framework for interactive visual applications based upon the principles of modeling 3D objects. PNS presents some preliminary efforts to enable the user to interact human and computer with each other.

• 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.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.12-19
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• 2003

This paper presents the effect of boundary conditions in various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the aid of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.2
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• pp.108-113
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• 2009

MFL(magnetic flux leakage) inspection is a general method of non-destructive evaluation(NDE) of underground gas pipelines. Pipelines are magnetized by permanent magnets when MFL PIG(pipeline inspection gauge) gets through them. If defects or corrosions exist in pipelines, effective thickness is changed and thus variation of leakage flux occurs. The leakage flux signals detected by hall-sensors are analyzed to characterize defect's geometries such as length, width, depth, and so on. This paper presents several methods for estimating defect's length using MFL signals and their performances are compared for real defects carved in KOGAS pipeline simulation facility. It is found that 80% and 90% of minimum values for axial and peak values for radial signals respectively show the best performance in the point of length estimation error.

• Proceedings of the KWS Conference
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• 2000.04a
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• pp.287-289
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• 2000

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.2
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• pp.122-129
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• 2006

Shearography is one of optical methods that has been applied to nondestructive testing (NDT) and strain/stress analysis. The technique has the merit of the directly measuring relative displacement, which is insensitive to environmental vibration disturbance. Previous studies about the method have emphasized on extending its application to new fields and lack insufficient research on effective parameters for qualitative and quantitative evaluation of defects. In this paper, the influence of shearing amount on the detection of an internal defect is investigated. In experiment, slender defects along longitudinal direction of pipeline are artificially designed and detection results according to the change of shearing amount are analyzed. Based on the investigation, we propose the technique for the determination of defect size and accurate source location.

• Journal of Mechanical Science and Technology
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• v.18 no.9
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• pp.1493-1499
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• 2004

This paper describes the speckle shearing interferometry, a non-destructive optical method, for quantitative estimation of void defect and monitoring separation defect inside of a pneumatic tire. Previous shearing interferometry has not supplied quantitative result of inside defect, due to effective factors. In the study, factors related to the details of an inside defect are classified and optimized with pipeline simulator. The size and the shape of defect can be estimated accurately to find a critical point and also is closely related with shearing direction. The technique is applied for quantitative estimation of defects inside of a pneumatic tire. The actual traveling tire is monitored to reveal the cause of separation and the starting points. And also unknown void defects on tread are inspected and the size and shape of defects are estimated which has good agreement with the result of visual inspection.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.343-350
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• 2016

Remaining lifetime prediction of the underground gas pipeline plays a key role in maintenance planning and public safety. One of main causes in the pipeline failure is metal corrosion. This paper deals with estimating the pipeline reliability in the presence of corrosion defects. Because a pipeline has uncertainty and variability in its operation, probabilistic approximation approaches such as first order second moment (FOSM), first order reliability method (FORM), second order reliability method (SORM), and Monte Carlo simulation (MCS) are widely employed for pipeline reliability predictions. This paper presents a fuzzy inference based reliability method (FIRM). Compared with existing methods, a distinction of our method is to incorporate a fuzzy inference into quantifying degrees of variability in corrosion defects. As metal corrosion depends on the service environment, this feature makes it easier to obtain practical predictions. Numerical experiments are conducted by using a field dataset. The result indicates that the proposed method works well and, in particular, it provides more advisory estimations of the remaining lifetime of the gas pipeline.