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.
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The authors would like to thank Mrs. N. Sonntag, BAM5.2, Berlin, Germany for carrying out tensile measurements and Dr. M. Pelkner, BAM 8.4, Berlin, Germany for fruitful technical discussion.
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Singh, W.S., Stegemann, R., Kreutzbruck, M. et al. Mapping of Deformation-Induced Magnetic Fields in Carbon Steels Using a GMR Sensor Based Metal Magnetic Memory Technique. J Nondestruct Eval 37, 21 (2018). https://doi.org/10.1007/s10921-018-0470-8
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DOI: https://doi.org/10.1007/s10921-018-0470-8