Determination Scheme for Accurate Defect Depth in Underground Pipeline Inspection by Using Magnetic Flux Leakage Sensors | IEEE Journals & Magazine | IEEE Xplore

Determination Scheme for Accurate Defect Depth in Underground Pipeline Inspection by Using Magnetic Flux Leakage Sensors


Abstract:

The magnetic flux leakage-type nondestructive testing has been applied for the highly efficient inspection of defects in ferromagnetic materials such as underground gas p...Show More

Abstract:

The magnetic flux leakage-type nondestructive testing has been applied for the highly efficient inspection of defects in ferromagnetic materials such as underground gas pipelines. In the system, the magnetic field is applied to magnetize a steel pipe so as to induce the leakage signal in the vicinity of defects on the pipe. From the measured sensor signals, decomposing or estimating sizes and shapes of defects are necessary. For the maintenance, the depth estimation is the most important procedure for the management of a safety accident. However, the previous depth estimation contains high error rate inevitably because the depth signal implies the width and length error simultaneously. This paper focused on the enhanced algorithm for the depth sizing in various defects by using the decoupling algorithm to enhance the accuracy of defect depth. Estimated results show good agreements with measured ones.
Published in: IEEE Transactions on Magnetics ( Volume: 54, Issue: 11, November 2018)
Article Sequence Number: 6202805
Date of Publication: 23 July 2018

ISSN Information:


I. Introduction

The magnetic flux leakage (MFL) method for nondestructive testing (NDT) has been applied for the inspection of defects in ferromagnetic materials such as natural gas pipelines [1]. The basic principle of the MFL method is that a strong magnetic field produced by the permanent magnet saturates the ferromagnetic pipeline to leak the magnetic field around the defect. Hall sensors equipped along the pipeline measure the magnetic leakage fields; then, the size of defects could be estimated by the measured signals [2], [3].

References

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