Effect of operational factors on magnetoacoustic emission of low-carbon steels

Skalsky, V.R.; Nazarchuk, Z. T.; Stankevych, Olena; Klym, B. P.; Selivonchyk, T.

doi:10.1016/j.ijpvp.2022.104744

Cited by 5 publications

(1 citation statement)

References 25 publications

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“…Recently, magnetoacoustic emission (MAE) techniques have received great attention in NDT for their high sensitivity to properties of ferromagnetic materials [13]. MAE refers to the acoustic emission generated during the magnetization of ferromagnetic materials [14,15], and it has been used to evaluate the mechanical properties of ferromagnetic materials, such as surface hardness [16,17], elastic deformation [18,19], plastic deformation [20][21][22], creep damage [23,24], and fatigue degree [25,26]. Due to the detection ability and generation mechanism of MAE being closely related, experiments have been widely performed to speculate on the generation mechanism of MAE.…”

Section: Introductionmentioning

confidence: 99%

Theoretical model of magnetoacoustic emission considering the microstructure of ferromagnetic material

Zhang,

Jiao,

et al. 2023

Meas. Sci. Technol.

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Magnetoacoustic emission (MAE) holds great promise for evaluating the mechanical properties of ferromagnetic materials. To refine the problems of the current theoretical and numerical models of MAE, a theoretical MAE model that considers the microscopic dependence of the hysteresis properties is proposed in this paper. The microstructure (dislocation density and grain size) and the correlation of MAE jumps are considered and incorporated into the model. Then, the influences of magnetization parameters and microstructure parameters on the envelope of the MAE signal are analyzed by the proposed theoretical model. The proposed theoretical model is then fully evaluated by simulations and experiments. The MAE experiments are conducted on ferromagnetic specimens with different hardnesses, and the MAE signals with different hardnesses are simulated by inverting the basic parameters of the MAE model with the genetic algorithm. Further, the crucial hysteresis parameters of the specimens are calculated using the results of microscopic measurements and the calculated parameters agree well with inversion results from experimental signals. The results demonstrate that the proposed theoretical model is valid for the MAE signal simulation. The trends of different hardnesses can be predicted by the MAE simulation signals. Moreover, the model can be used for theoretical analysis of the microscopic dependence of the MAE signal.

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