• 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.

• Journal of Mechanical Science and Technology
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• v.15 no.2
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• pp.232-238
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• 2001

Fast Fourier Transformation is employed to convert the head variation of a pipeline in the time domain to the amplitude of the frequency domain. Applying method of characteristics to a pipeline provides a significant frequency range for a surge introduced from the valve modulation. Inverse Fast Fourier Transformation and a Finite Impulse Response Filter can be used to remove any possible noise existing from the significant frequency range of an unsteady condition. A filtered signal shows higher potential for the inverse calculation of leakage detection than the noise-added signal does. The respective performances of Inverse Fast Fourier Transformation and a Finite Impulse Response Filter are compared in terms of leakage detection capability. Characteristics of the frequency range for multiple leakages were investigated to validate the effectiveness of the noise control method in the frequency domain.

• 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.

• 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.

• Journal of Korean Society of Water and Wastewater
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• v.31 no.5
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• pp.459-469
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• 2017

A real scale leakage test facility was developed to study the leak signal characteristics of water supply pipelines, and then leak tests were carried out. The facility was designed to overcome the limited experimental circumstances of domestic water supply pipeline experimental facilities. The length of the pipeline, which was installed as a straight line, is 280m. Six pipes were installed on a 70m interval with different pipe material and diameters that are DCIP(D200, D150, D100, D80), PE(D75) and PVC(D75).The intensity of the leakage is adjusted by changing the size of the leak hole and the opening rate of ball valve. Various pressure conditions were simulated using a pressure reducing valve.To minimize external noise sources which, deteriorate the quality of measured leak signal, the facility was built at a quiet area, where traffic and water consumption by customers is relatively rare. In addition, the usage of electric equipment was minimized to block out noise and the facility was operated using manual mode. From the experimental results of measured leakage signal at the facility, it was found that the signal intensity weakened and the signal of high frequency band attenuated as the distance from the water leakage point increased.

• Journal of the Korean Institute of Gas
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• v.6 no.1 s.17
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• pp.10-16
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• 2002

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.

• 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 Korean Society of Environmental Engineers
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• v.27 no.10
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• pp.1065-1071
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• 2005

Many techniques of leak detection in pipeline systems have developed based on the propagation wave speeds and wave attenuation. In this paper, the transient analysis methodology is used for calculating the wave speed in the plastic pipe and a frequency analysis methodology is developed for leakage detection in water pipe networks. Data acquisition system for pressurized pipeline system were designed md fabricated to obtain high frequency pressure data. The methodology properly handles the unavoidable uncertainties in measurement and modeling error. Based on information from head pressure test data, it provides leak prediction capability from the transient events with leakage.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.2
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• pp.139-147
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• 2020

This paper suggests a nonlinear pressure consideration scheme through an unsteady pipe network analyzer for leakage detection with a portable pressure wave generator. In order to evaluate the performance of a proposal scheme, linear input pattern has been simulated and experiments had been carried out under both no leakage and one leakage conditions in a reservoir-pipeline-valve system. This method using portable pressure wave generator showed that a leakage can be detected from a reflection where a leakage is originated through time domain analysis. Meaningful similarity in pressure response between nonlinear input pattern and experimental results were found both no leakage and a leakage conditions.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.571-578
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• 2018

The deteriorated pipline often causes the unexpected leakage and crack. Negligence and late maintenance leads the enormous damage for gas and water resource. This paper proposes early fault detection and diagnosis algorithm for pipeline using acoustic emission (AE) signals. Early fault detection method for pipeline compares the frequency amplitude of the spectrum to that of the spectrum in normal condition. Larger amplitude of the spectrum indicates abnormal condition. Early fault diagnosis algorithm uses support vector machines (SVM), which is trained for normal and abnormal conditions to diagnose the measured AE signal from the target pipeline. In the experiment, a pipeline testbed is constructed similarly to real industrial pipeline. Normal, 5mm cracked, 10mm holed pipelines are installed and tested in this study. The proposed fault detection and diagnosis technique is validated as an efficient approach to detect early faulty condition of pipeline.