Influence of Tensile Stress on the Surface Magneto-Optical Hysteresis Loops in Amorphous and (Nano)Crystalline Ribbons

Životský, Ondřej; Hendrych, Aleš

doi:10.1109/tmag.2013.2286406

Cited by 5 publications

(2 citation statements)

References 16 publications

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“…Present studies are devoted to applying the Becker-Kersten method in the evaluation of magnetic characteristics measured in the close surface layers of the amorphous Fe 73 Co 12 B 15 amorphous ribbon using magneto-optical Kerr microscopy. The first possibilities to find local surface λ s using the magneto-optical Kerr effect were published in [10]. Because the surface magnetic properties of amorphous ribbons are often locally inhomogeneous, the visualization of the place on the surface into which the laser spot was focused was difficult.…”

Section: Introductionmentioning

confidence: 99%

Surface Magnetostriction of FeCoB Amorphous Ribbons Analyzed Using Magneto-Optical Kerr Microscopy

et al. 2020

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Surface sensitive magneto-optical Kerr microscopy completed with the special self-made sample holder is used for studying the magneto-elastic behaviour in the surface of the as-quenched amorphous Fe73Co12B15 alloy. The 10, 5, and 3 mm wide and approximately 34 μm thick ribbons were prepared by the conventional planar flow casting process. The experimental setup allows for a simultaneous application of an external magnetic field in the directions parallel and perpendicular to the ribbon axis and of compression stress from one side of the sample, resulting in tensile stress in opposite side. The distributions of tensile stresses in the measured surface were modelled by the finite element method. The observed changes of the magnetic domains and hysteresis loop anisotropy field under applied stress are evaluated using the Becker–Kersten method. This resulted in the determination of the local surface magnetostrictive coefficient from an area of about 200 μm in diameter. The obtained values ranged between 37–60 ppm and were well comparable with the bulk value presented in the literature.

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Section: Introductionmentioning

confidence: 99%

Surface Magnetostriction of FeCoB Amorphous Ribbons Analyzed Using Magneto-Optical Kerr Microscopy

et al. 2020

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“…A tensile force applied to a steel rod changes its magnetic properties [3][4][5][6]. Thus, the hysteresis loop measured from the steel rod varies with the tensile force [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Prediction of the tensile force applied on surface-hardened steel rods based on a CDIF and PSO-optimized neural network

Zhu

Sun

et al. 2018

Meas. Sci. Technol.

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The features traditionally extracted from hysteresis loops are highly sensitive to both the variation of case depth and uncontrollable factors in repeated testing cycles, thus increasing the difficulty in predicting the tensile force applied on surface-hardened steel rods with different case depths. In this study, in order to eliminate the influence of such high sensitivity, a case depth-insensitive feature (CDIF) was proposed to characterize the tensile force, and a particle swarm optimization (PSO)-optimized neural network was used to establish the correlation between the CDIF and tensile force in order to predict the tensile force applied on steel rods with different case depths. Five classical features (including remanent magnetic induction intensities, coercive force, hysteresis loss, maximum magnetic induction, and distortion factor) and the CDIF were successfully used to characterize the tensile force. Then, the linear regression model and PSO-optimized neural network model were used in turn to establish the relationship between each feature and tensile force to predict the tensile force applied on steel rods with different case depths. The CDIF was insensitive to the variation of case depth and linearly correlated with the tensile force. Even though the CDIF is affected by the unknown and uncontrollable factors in repeated testing cycles, the PSO-optimized neural network model based on it can be used to accurately predict the tensile force applied on steel rods with different case depths with a prediction error of 0.67%.

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Vibration reduction method of switched reluctance motors with amorphous alloy cores based on inverse-magnetostriction effect

Ben

Wang²,

Chen³

et al. 2022

J. Power Electron.

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Influence of Tensile Stress on the Surface Magneto-Optical Hysteresis Loops in Amorphous and (Nano)Crystalline Ribbons

Cited by 5 publications

References 16 publications

Surface Magnetostriction of FeCoB Amorphous Ribbons Analyzed Using Magneto-Optical Kerr Microscopy

Surface Magnetostriction of FeCoB Amorphous Ribbons Analyzed Using Magneto-Optical Kerr Microscopy

Prediction of the tensile force applied on surface-hardened steel rods based on a CDIF and PSO-optimized neural network

Vibration reduction method of switched reluctance motors with amorphous alloy cores based on inverse-magnetostriction effect

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