Low alloyed steels of low, medium, or high strength are frequently used for many applications in the automotive, civil (bridges), aerospace, and petrochemical industries. A variety of thermomechanical regimes, in which these steels can be produced, enable customization of their matrix with respect to their fatigue resistance, resistance against friction and impact wear, fracture toughness, corrosion resistance, etc. This study analyses the influence of magnetising conditions on Barkhausen noise and other extracted parameters. It was found that the increasing magnetising frequency makes Barkhausen noise weaker, especially in the high strength low alloyed steels, as a result of the decreasing magnetic field in a sample. For this reason, increasing fraction of domain walls is unpinned at the higher frequencies. Barkhausen noise for the high strength low alloyed steels at higher frequencies is remarkably attenuated. Moreover, the different behaviour with respect to direction of the sheet rolling and the transversal direction, can be found due to realignment of the domain walls. This study demonstrates that the position of Barkhausen noise envelopes and the number of Barkhausen noise pulses increase in a systematic manner at the lower magnetising frequencies. Those parameters can be employed for distinction of the low alloyed steels, investigated in this study. However, the increasing magnetising frequency makes attenuation of Barkhausen noise more remarkable for the low alloyed steels of the higher strength. Therefore, the effective value of Barkhausen noise, at the magnetising frequency 750 Hz, in the rolling direction exhibits the systematic descent along with the increasing yield strength. This parameter can be used for distinction of the low alloyed steels after their thermomechanical processing, as well.
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http://dx.doi.org/10.3390/ma15207239 | DOI Listing |
Sensors (Basel)
November 2024
School of Mechanical Engineering, Inner Mongolia University of Science and Technology, Baotou 014010, China.
Magnetic Barkhausen noise (MBN) is one of the most effective methods for determining the easy axis of ferromagnetic materials and for evaluating texture and residual stress in a nondestructive manner. MBN signals from multiple angles and different magnetization sections can be used to characterize magnetic anisotropy caused by various magnetization mechanisms. This paper reviews the development and application of magnetic anisotropy detection technology, and the MBN anisotropy models that take into account domain wall motion and magnetic domain rotation are analyzed thoroughly.
View Article and Find Full Text PDFMaterials (Basel)
October 2024
Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Trojanova 13, 120 00 Prague, Czech Republic.
This paper deals with Barkhausen noise in Trip steel RAK 40/70+Z1000MBO subjected to uniaxial plastic straining under variable strain rates. Barkhausen noise is investigated especially with respect to microstructure alterations expressed in terms of phase composition and dislocation density. The effects of sample heating and the corresponding Taylor-Quinney coefficient are considered as well.
View Article and Find Full Text PDFMaterials (Basel)
September 2024
Serwistal Sp. z.o.o., 2A Dojazdowa Str., 19-300 Ełk, Poland.
Among non-destructive testing methods, a group dedicated to the assessment of the state of residual stresses can be distinguished. The method of measuring residual stresses using the Barkhausen noise method has many advantages, as evidenced by the number of publications. The residual stresses in metal products are important for the further processing of such metal, such as laser cutting or bending.
View Article and Find Full Text PDFMaterials (Basel)
May 2024
Central Research Institute of Baosteel, Shanghai 201999, China.
Both microstructure and stress affect the structure and kinematic properties of magnetic domains. In fact, microstructural and stress variations often coexist. However, the coupling of microstructure and stress on magnetic domains is seldom considered in the evaluation of microstructural characteristics.
View Article and Find Full Text PDFSensors (Basel)
March 2024
Department of information, Beijing University of Technology, Beijing 100124, China.
The correlation between magnetic Barkhausen noise (MBN) features and the surface hardness of two types of die steels (Cr12MoV steel and S136 steel in Chinese standards) was investigated in this study. Back-propagation neural network (BP-NN) models were established with MBN magnetic features extracted by different methods as the input nodes to realize the quantitative prediction of surface hardness. The accuracy of the BP-NN model largely depended on the quality of the input features.
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