• Proceedings of the KSME Conference
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• 2001.06b
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• pp.235-240
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• 2001

This paper introduces developed prototype intelligent pig which detects corrosion on pipeline by using Magnetic Flux Leakage technology. The 8 inch developed MFL(Magnetic Flux Leakage) pig is composed of 5 yokes which magnetize pipeline wall and 45 Hall sensors which detect MFL signal. The designed MFL modules are analyzed by using magnetic circuit method in order to confirm whether pipeline wall is fully saturated. A variety of artificial defects are manufactured on 8 inch diameter steel pipeline in order to acquire MFL signals. So leakage flux of the axial, radial and circumferential component was acquired as defects. The results of this paper show that design technique for 8 inch MFL pig can be applied to large diameter MFL pig and 0.5mm defect depth can be detected.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.2
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• pp.48-54
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• 2000

This paper presents the effect of shape of external corrosion in pipeline on failure prediction by using a numerical simulation. The numerical study for the pipeline failure analysis is based on the FEM(Finite Element Method)with an elastic-plstic and large-deformation analysis. Corrosion pits and narrow corrosion grooves in pressurized pipeline were analysed. A failure criterion, based on the local stress state at the corrosion and a plastic collapse failure mechanism, is proposed. The predicted failure stress assessed for the simulated corrosion defects having different corroded shapes along the pipeline axis compared with those by methods specified in ANSI/ASME B31G code and a modified B31G code. It is concluded the corrosion geometry significantly affects the failure behavior of corroded pipeline and categorisation of pipeline corrosion should be considered in the development of new guidance for integrity assessment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1086-1103
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• 2020

The automatic identification and classification of image-based weld defects is a difficult task due to the complex texture of the X-ray images of the weld defect. Several depth learning methods for automatically identifying welds were proposed and tested. In this work, four different depth convolutional neural networks were evaluated and compared on the 1631 image set. The concavity, undercut, bar defects, circular defects, unfused defects and incomplete penetration in the weld image 6 different types of defects are classified. Another contribution of this paper is to train a CNN model "RayNet" for the dataset from scratch. In the experiment part, the parameters of convolution operation are compared and analyzed, in which the experimental part performs a comparative analysis of various parameters in the convolution operation, compares the size of the input image, gives the classification results for each defect, and finally shows the partial feature map during feature extraction with the classification accuracy reaching 96.5%, which is 6.6% higher than the classification accuracy of other existing fine-tuned models, and even improves the classification accuracy compared with the traditional image processing methods, and also proves that the model trained from scratch also has a good performance on small-scale data sets. Our proposed method can assist the evaluators in classifying pipeline welding defects.

• Journal of the Korean Institute of Gas
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• v.14 no.4
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• pp.31-36
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• 2010

An alternative method is presented for predicting failure probability of pipelines with corrosion defects in this paper. The failure of corroded pipeline occurs when the operating pressure is grater than the remaining strength of the pipeline, and a limit state function can be defined as the differences between the remaining strength and the operating pressure. Then, based on structural reliability theory, we can estimate the failure probability of corroded pipeline, which is dependent on elapsed time of the pipeline with active corrosion defects. In this study, a root finding (RF) method has been adopted to solve the limit state function instead of Monte-Carlo simulation (MCS) method which traditionally has been employed to solve those kinds of problems. The calculation results shows that there are only small differences between the RF and the MCS method but the RF has higher efficiency in calculation than the MCS.

• Corrosion Science and Technology
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• v.4 no.4
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• pp.164-170
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• 2005

Pipelines have the highest capacity and are the safest and the least environmentally disruptive means for transmitting gas or oil. Recently, failures due to corrosion defects have become a major concern in maintaining pipeline integrity. A number of solutions have been developed for the assessment of remaining strength of corroded pipelines. In this paper, a Fitness-For-Purpose(FFP) type limit load solution for corroded city gas pipelines is proposed. For this purpose, a series of burst tests with various types of machined defects were performed. Finite element simulations were carried out to derive an appropriate failure criterion. Based on such solution along with existing solutions, an integrity evaluation program for corroded city gas pipeline, COPAP-CITY, has been developed.

• 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.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 1998.11a
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• pp.261-266
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• 1998

This paper presents a numerical simulation of the failure behaviour for the pipeline which has external corroded parts along the axis. The numerical study for the pipeline failure analysis is based on an FEM with an elastic-plastic and large-deformation. The predicted failure assessments for the simulated corrosion defects are compared with ANSI/ASME B31G code and a modified B31G method.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.1-6
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• 2000

FFP(Fitness For Purpose) type defect assessment methodologies based on ECA(Engineering Critical Analysis) have been established and are in use for the structural integrity evaluation of gas pipelines. ECA usually includes the fracture mechanics analysis, and it assumes that J-integral uniquely characterizes crack-tip stress-strain fields. However, it has been shown that it is not sufficient to characterize the crack-tip field under low levels of constraint with a single parameter. Since pipeline structures are made of ductile material, locally loaded in tension, cracks may experience low level of constraint, and therefore, J-dominance will be lost. For this reason, the level of constraint must be quantified to establish a precise assessment procedure for pipeline defects. The objective of this paper is to Investigate the fracture behavior of a crack in gas pipeline by quantifying the level of constraint. For this purpose, tensile tests and CTOD tests were performed at room temperature$(24^{\circ}C)$ and low temperature$(-40^{\circ}C)$ to obtain the material properties. J-Q analyses were performed for SENB and SENT specimens based on 2-D finite element analyses, in order to investigate the in-plane constraint effects on pipeline defects.

• 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.

• Journal of Mechanical Science and Technology
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• v.16 no.7
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• pp.889-895
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• 2002

This paper presents the effect of external corrosion, material properties, operation condition and design thickness in pipeline on failure prediction using a failure probability model. The predicted failure assessment for the simulated corrosion defects discovered in corroded pipeline is compared with that determined by ANSI/ASME B31G code and a modified B31G method. The effects of environmental, operational, and random design variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress and pipe thickness on the failure probability are systematically studied using a failure probability model for the corrosion pipeline.