Identification of Grain Oriented SiFe Steels Based on Imaging the Instantaneous Dynamics of Magnetic Barkhausen Noise Using Short-Time Fourier Transform and Deep Convolutional Neural Network

This paper presents a new approach to the extraction and analysis of information contained in magnetic Barkhausen noise (MBN) for evaluation of grain oriented (GO) electrical steels. The proposed methodology for MBN analysis is based on the combination of the Short-Time Fourier Transform for the observation of the instantaneous dynamics of the phenomenon and deep convolutional neural networks (DCNN) for the extraction of hidden information and building the knowledge. The use of DCNN makes it possible to find even complex and convoluted rules of the Barkhausen phenomenon course, difficult to determine based solely on the selected features of MBN signals. During the tests, several samples made of conventional and high permeability GO steels were tested at different angles between the rolling and transverse directions. The influences of the angular resolution and the proposed additional prediction update algorithm on the DCNN accuracy were investigated, obtaining the highest gain for the angle of 3.6°, for which the overall accuracy exceeded 80%. The obtained results indicate that the proposed new solution combining time–frequency analysis and DCNN for the quantification of information from MBN having stochastic nature may be a very effective tool in the characterization of the magnetic materials.

Magnetic Barkhausen Noise Transient Analysis for Microstructure Evolution Characterization with Tensile Stress in Elastic and Plastic Status

Stress affects the microstructure of the material to influence the durability and service life of the components. However, the previous work of stress measurement lacks quantification of the different variations in time and spatial features of micromagnetic properties affected by stress in elastic and plastic ranges, as well as the evolution of microstructure. In this paper, microstructure evolution under stress in elastic and plastic ranges is evaluated by magnetic Barkhausen noise (MBN) transient analysis. Based on a J-A model, the duration and the intensity are the eigenvalues for MBN transient analysis to quantify transient size and number of Barkhausen events under stress. With the observation of domain wall (DW) distribution and microstructure, the correlation between material microstructure and MBN transient eigenvalues is investigated to verify the ability of material status evaluation on the microscopic scale of the method. The results show that the duration and the intensity have different change trends in elastic and plastic ranges. The eigenvalue fusion of the duration and intensity distinguishes the change in microstructure under the stress in elastic and plastic deformation. The appearance of grain boundary (GB) migration and dislocation under the stress in the plastic range makes the duration and the intensity higher on the GB than those inside the grain. Besides, the reproducibility of the proposed method is investigated by evaluating microstructure evolution for silicon steel sheet and Q235 steel sheet. The proposed method investigates the correlation between the microstructure and transient micromagnetic properties, which has the potential for stress evaluation in elastic and plastic ranges for industrial materials.

Experimental Consideration of Conditions for Measuring Residual Stresses of Rails Using Magnetic Barkhausen Noise Method

Residual stress, a factor affecting the fatigue and fracture characteristics of rails, is formed during the processes of fabrication and heat treatment, and is also generated by vertical loads on wheels due to the weight of vehicles. Moreover, damage to rails tends to accelerate due to the continuous increase in the number of passes and to the high speed of passing vehicles. Because this can have a direct effect on safety accidents, having a technique to evaluate and analyze the residual stresses in rails accurately is very important. In this study, stresses due to tensile loads applied to new rails and residual stresses remaining in used rails were measured by using magnetic Barkhausen noise method. First, a magnetization frequency and noise band suitable for the rails were selected. Moreover, by applying tensile loads to specimens and comparing the difference in magnetization amplitudes for each load, the stresses applied to the rails by using the magnetic Barkhausen noise method were measured, and the analysis of the results was verified. Based on these results, the difference in the results for the loads asymmetrically applied according to the wheel shape was analyzed by measuring for the head parts of used rails.

Evaluating Temper Embrittlement in HY-80 Steel Using Magnetic Barkhausen Noise and Microstructural Characterization

HY80 steel is a low-carbon steel known for embodying high strength and toughness properties. This steel is used in submarine applications. Temper embrittlement, which is the reduction of fracture toughness, occurs in steels when subject to aging and drastic temperature fluctuations. These changes occur in submarines over time while in underwater environments. During temper embrittlement, impurity atoms and carbides migrate to grain boundaries, which make the steel more susceptible to fracture. A non-destructive testing (NDT) method is desirable to assess the temper embrittlement damage in HY80. Magnetic Barkhausen Noise (MBN) is of interest as being a potential NDT method for analyzing HY80. Focusing on microstructural characterization and its effect on MBN could have implications for establishing an MBN based method to detect varied stages of temper embrittlement in HY80 steel. In this research, samples of HY80 were prepared and heat treated for 16–336 hours to mimic various degrees of temper embrittlement. Microstructural changes with heat treatment were characterized and connected to the MBN produced at each holding time. Methods consisted of performing scanning electron microscopy (SEM) and using an MBN measurement system. It was observed that as holding time increases, grain size increases and carbide density within the grains decreases. These carbides, which act as pinning sites, make it more difficult for domain walls to move, consequently affecting MBN energy.