Mapping of Deformation-Induced Magnetic Fields in Carbon Steels Using a GMR Sensor Based Metal Magnetic Memory Technique

Mapping of Deformation-Induced Magnetic Fields in Carbon Steels Using a GMR Sensor Based Metal... Giant magneto-resistive (GMR) sensor based metal magnetic memory (MMM) technique is proposed for mapping of deformation-induced self-magnetic leakage fields (SMLFs) in carbon steel. The specimens were subjected to different amounts of tensile deformation and the deformation-induced SMLFs were measured using a GMR sensor after unloading the specimens. 3D-nonlinear finite element modeling was performed to predict stress–strain state in a steel specimen under tensile load. The experimentally obtained SMLF images were correlated with the finite element model predicted stress–strain states. Studies reveal that the MMM technique can detect the plastic deformation with signal-to-noise ratio better than 20 dB. The technique enables the mapping of plastic deformation in carbon steels for the evaluation of the severity of deformation. The study also reveals that deformation-induced SMLF is influenced by the presence of initial surface residual stress, introduced by shot peening. The intensity of SMLF signal is found to increase with increase in tensile load and decrease with shot peening. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Nondestructive Evaluation Springer Journals

Mapping of Deformation-Induced Magnetic Fields in Carbon Steels Using a GMR Sensor Based Metal Magnetic Memory Technique

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Engineering; Structural Mechanics; Characterization and Evaluation of Materials; Vibration, Dynamical Systems, Control; Classical Mechanics
ISSN
0195-9298
eISSN
1573-4862
D.O.I.
10.1007/s10921-018-0470-8
Publisher site
See Article on Publisher Site

Abstract

Giant magneto-resistive (GMR) sensor based metal magnetic memory (MMM) technique is proposed for mapping of deformation-induced self-magnetic leakage fields (SMLFs) in carbon steel. The specimens were subjected to different amounts of tensile deformation and the deformation-induced SMLFs were measured using a GMR sensor after unloading the specimens. 3D-nonlinear finite element modeling was performed to predict stress–strain state in a steel specimen under tensile load. The experimentally obtained SMLF images were correlated with the finite element model predicted stress–strain states. Studies reveal that the MMM technique can detect the plastic deformation with signal-to-noise ratio better than 20 dB. The technique enables the mapping of plastic deformation in carbon steels for the evaluation of the severity of deformation. The study also reveals that deformation-induced SMLF is influenced by the presence of initial surface residual stress, introduced by shot peening. The intensity of SMLF signal is found to increase with increase in tensile load and decrease with shot peening.

Journal

Journal of Nondestructive EvaluationSpringer Journals

Published: Feb 21, 2018

References

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