Magnetic Barkhausen Noise Analysis Research Articles

An improved hidden Markov model with magnetic Barkhausen noise and optimized Gaussian mixture feature for fatigue prediction

Evaluating fatigue states of metallic materials is essential for predicting their failures and ensuring structural safety. Magnetic Barkhausen noise (MBN) analysis, a non-destructive testing method, provides efficient and reliable methods for identifying and categorising material parameters such as hardness and residual stresses. To establish a quantitative relationship between MBN signals and fatigue states, an improved hidden Markov model (HMM) is proposed based on optimised Gaussian mixture features (GMFs) and the Kullback–Leibler (KL) divergence measure for fatigue prediction. The MBN-GMFs replicate the probability characteristics of MBN signals and track the fatigue degradation trend throughout the fatigue life; thus, they are superior to some widely used statistical features. A Gaussian component optimisation algorithm is proposed to automatically adjust the appropriate number of components in the Gaussian mixture model and enhance the representation of MBN-GMFs. Then, the KL divergence is introduced to quantify the similarity and accurately classify the degree of MBN-GMF migration. The HMM is constructed to obtain the probability transfer relationship between the observations and states and obtain accurate fatigue predictions. Experiments on two 20R metallic materials at three excitation frequencies are conducted to collect the MBN signals. The experimental results and comparisons indicate that the proposed HMM can accurately predict fatigue states and provide a practical and robust analysis tool for MBN-based fatigue predictions.

Subsurface conditioning in BTA deep hole drilling for improved component performance

When bores with high length-to-diameter ratios (l/D > 10) and large diameters (D > 40 mm) are required, usually, the Boring and Trepanning Association (BTA) deep hole drilling process is used. Common industrial applications of this process are aerospace engineering and petrol exploration, where drilled components range from landing gears and engine shafts to drill collars. Since such parts tend to be particularly costly and highly safety–critical, ensuring favorable surface integrity during drilling is crucial to guarantee their reliability and performance. This study aims to identify correlations between the BTA deep hole drilling process and the resulting surface integrity using experimental and simulative approaches. The impact of feed and cutting speed on the thermomechanical loads and the resulting surface integrity are analyzed, also taking into account the occurrence of dynamic process disturbances. Particularly, the formation of white etching layers (WEL) is investigated using well-established, conventional techniques such as optical microscopy and microhardness testing. Additionally, innovative micromagnetic methods are employed. Magnetic Barkhausen noise (MBN) analysis is qualified as a well-applicable approach for rapid, non-destructive detection of WEL. To enhance understanding of MBN analysis and increase its robustness, the underlying mechanisms, governing the magnetic behavior of the subsurface are elucidated in detail by X-ray diffraction (XRD), electron backscatter diffraction (EBSD), magnetic force microscopy (MFM) and magneto-optical Kerr effect (MOKE) microscopy. The methodology will serve as a basis for controlled subsurface conditioning in BTA deep hole drilling.

Study of the ability of MBN based NDT to distinguish high-performance martensitic steel grades

The interest of non-destructive testing (NDT) in steel material characterization is growing especially for quality and life cycle control. The Magnetic Barkhausen Noise (MBN) analysis shows an extreme sensitivity to different parameters: steel grade, grain size, microstructure, magnetic domains wall structure, residual stress, surface condition, etc. It is very difficult to distinguish the individual effect of each parameter on the steel MBN signature. This paper attempts to address this problematic by fixing most of these parameters and varying only one parameter of interest (either austenitizing or tempering temperature) to assess the ability of the MBN technique to dissociate the mechanical properties of different martensitic steel grades. The MBN technique presented herein has proven to be able to distinguish high-performance martensitic steel grades when applied according to the proposed experimental protocol.

Stress measurement based on magnetic Barkhausen noise for thin films

Non-destructive testing methods based on magnetic Barkhausen noise (MBN) are expected to be applied to thin films. Recently, MBN analysis using machine learning has been performed on bulk materials and used as an in-situ stress and material evaluation method. However, for thin films, it is difficult to measure due to the weak MBN signal intensity, and few examples of its use as a stress and material evaluation method have been reported. This study acquired and analyzed MBN of FeCo polycrystalline thin films under bending stress. After pre-processing the acquired MBNs, two representative machine learning algorithms were used to learn the relationship between MBN and stress. By quantitatively comparing the prediction accuracy of each machine learning method, the characteristics of the MBN-based stress evaluation method were discussed from two perspectives: the need for domain knowledge and its applicability to unknown data. This study provides insight into machine learning-assisted MBN analysis as a stress evaluation method for thin films. The extension of MBN-based stress evaluation methods to thin films could be applied to the non-destructive stress evaluation of micro- and nanostructures, where stress state is critical, and could improve process development efficiency.

Grinding Burn Detection via Magnetic Barkhausen Noise Analysis Independently of Induction Hardened Depth

The electromagnetic technique based on magnetic Barkhausen noise (MBN) can be used to control the quality of ball screw shafts non-destructively, although identifying any slight grinding burns independently of induction-hardened depth remains a challenge. The capacity to detect slight grinding burns was studied using a set of ball screw shafts manufactured by means of different induction hardening treatments and different grinding conditions (some of them under abnormal conditions for the purpose of generating grinding burns), and MBN measurements were taken in the whole group of ball screw shafts. Additionally, some of them were tested using two different MBN systems in order to better understand the effect of the slight grinding burns, while Vickers microhardness and nanohardness measurements were taken in selected samples. To detect the grinding burns (both slight anddata intense) with varying depths of the hardened layer, a multiparametric analysis of the MBN signal is proposed using the main parameters of the MBN two-peak envelope. At first, the samples are classified into groups depending on their hardened layer depth, estimated using the intensity of the magnetic field measured on the first peak (H1) parameter, and the threshold functions of two parameters (the minimum amplitude between the peaks of the MBN envelope (MIN) and the amplitude of the second peak (P2)) are then determined to detect the slight grinding burns for the different groups.

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.

Angular magnetic Barkhausen noise of incline- and cross-rolled non-oriented electrical steel sheets

Magnetic Barkhausen noise (MBN) analysis is a relatively new technique used to characterize the magnetic properties of electrical steels. Not only has it been utilized to evaluate the overall core loss of electrical steel sheets, but it has also been employed as a non-destructive testing (NDT) tool to assess the magnetocrystalline anisotropy of ferromagnetic materials. In this study, non-oriented electrical steel sheets produced by inclined and cross rolling were characterized by both MBN and electron backscatter diffraction (EBSD). The angular MBN measured on the surface of the steel sheet was directly compared to the magnetocrystalline anisotropy energy (MAE) calculated from the measured crystallographic texture. The MBN energy corresponding to the saturation-to-remanence part of the hysteresis loop was evaluated, which had been reported to have a close correlation to the MAE in pipeline steels. The results in this study showed that such a relationship did not exist in any of the electrical steel samples examined (including deformed, partially recrystallized, and completely recrystallized), although in some samples the polarities of the MBN and MAE partially coincide. It was shown that the residual stress in the material played an important role in determining the polarities of the angular MBN, which had been ignored in the previous studies when comparing the MBN to the MAE. Possible reasons that caused the discrepancies between the results of this study and those of the previous studies were given.

Effect of niobium and molybdenum addition on the wear resistance and the rolling contact fatigue of railway wheels

Brazilian heavy-haul railway companies have drawn extensive research in the last years for developing solutions that can make the operation in this area more efficient and safer, such as friction management, the use of new mechanical assemblies, and the use of new materials for wheels and rails. Another solution implemented is increasing the weight transported by train wagons; however, the more weight added, the more deterioration caused to wheels and rails, for example, promoting higher maintenance costs and risks to safety. Thus, the key to extending the life cycle of railroad wheels is to reduce the wear and rolling contact fatigue (RCF) in developing new materials and in manufacturing them. Niobium (Nb) and molybdenum (Mo) are usually added to increase the mechanical strength of pearlitic steels by decreasing the interlayer spacing. This way, comparative twin-disc test for wheel material under dry conditions was performed to verify the wear resistance of a commercial railway wheel (7C) and a newly developed class D railway wheel steel (7 M) with Nb and Mo addition. Following the specifications of the Association of American Railroads (AAR) standard, a twin-disc tribometer with automatic control of load and speed was used. The slip ratio was obtained from the difference between the axis rotation. 7 M steel was observed to present lower mass loss compared with 7C steel. The Magnetic Barkhausen noise analysis showed higher residual stress close to the surface for 7 M steel, which correlated with the work-hardened depth. Such results, therefore, indicate that 7 M steel presented better performance than 7C steel regarding the specific characteristics of the tests. To confirm the feasibility of the wheel material for use in service, further twin-disc tests are proposed for both wheel materials (7 M & 7C) against the same rail material.

Potential of magnetic Barkhausen noise analysis for in-process monitoring of surface layer properties of steel components in grinding

Abstract Grinding processes are often the last step in the value-added chain of high-performance hardened steel components. However, thermo-mechanical loads which can take place during the process can have a detrimental effect on the surface integrity of ground parts, which are generally tested by post-process measurements. In the present study, two different approaches for an in-process inspection of the workpiece surface integrity were assessed using magnetic Barkhausen noise analysis during cylindrical grinding of hardened workpieces. The results showed that both measuring systems are able to detect changes in the surface state of workpieces in-process or directly after grinding in the grinding machine. After preparations to protect the sensors from influences during the grinding process, changes in the residual stress state and a decrease of hardness could be reliably detected. Due to constant contact conditions between sensor and workpiece a high reproducibility of the measurements was achieved.

Influence of cutting parameters on the formation of white etching layers in BTA deep hole drilling

Abstract In this study, the influence of cutting speed and feed rate on surface integrity in Boring Trepanning Association (BTA) deep hole drilling of AISI 4140+QT is investigated. Microstructure and micro-hardness in the subsurface zones of bores are analyzed, using metallographic and micromagnetic methods. It was found that when using high feed rates and cutting speeds, white etching layers (WEL) form at the surface of the bores. These layers are up to three times harder than the substrate material and have a maximum thickness of approx. t WEL ≈ 12 µm {t_{\mathrm{WEL}}}\approx 12\hspace{0.1667em}\text{\textmu m} . WEL were usually followed by a transitional layer, so that elevated hardness was observed until a depth of d surf = 35 µm {d_{\mathrm{surf}}}=35\hspace{0.1667em}\text{\textmu m} below the surface. Magnetic Barkhausen noise (MBN) analysis proved to be applicable for the fast and reliable detection of WEL. The presented results contribute to gaining a deeper understanding of the complex interrelations between the design of the BTA process, the resulting microstructure in the machined component and the properties of the conditioned surface. Based on discovered correlations, a dynamic process control will be developed for BTA deep hole drilling, which will allow reliably tailoring surface integrity of components to specific demands, like an optimized fatigue performance.

Wear behavior of bainitic and pearlitic microstructures from microalloyed railway wheel steel

Wear and contact fatigue are the main problems that reduce the durability of the rail and wheels. Pearlitic and bainitic microstructures have been studied over the years to obtain steel with higher mechanical properties, minimizing the wear and fatigue defects. However, the studies have not yet consistently confirmed whether bainite is a better alternative than pearlite to reduce the wear and contact fatigue. Therefore, in this paper, the twin-disc test evaluated, under dry conditions, the wear resistance and rolling contact fatigue (RCF) of bainitic and pearlitic microstructures obtained from forged microalloyed railway wheel steel. The samples were isothermally treated in furnace at 350 and 600 °C, respectively, and the tests had controlled load and slip conditions. Thus, the bainitic microstructure presented lower mass loss than the pearlitic one, having higher hardness and greater capacity to absorb plastic deformation in volume. Also, it took the delamination process longer to develop in the bainitic microstructure, and the cracks were closer to the surface than in the pearlitic microstructure. After the wear test, the magnetic Barkhausen noise (MBN) analysis indicated higher levels of stress in the bainitic microstructure surface than in the pearlitic one. These findings suggest that the high concentration of plastic deformation closer to the surface prevented crack nucleation and propagation to greater depths. Thus, this study supports the suggestion that the bainitic microstructure may be a better alternative than pearlitic microstructure concerning railway wheel production.

Effect of Gas Metal Arc Welding on Magnetic Response of Ferritic Stainless Steel

The variation of magnetic Barkhausen noise (MBN) response of different regions of the gas metal arc welded ferritic stainless steel SS409L plate in terms of number of pulses and root mean square value with the variation of MBN analysis parameters (magnetic field intensity and magnetizing frequency) have been investigated in the present work. Five different values of magnetic field intensity 250, 500, 750, 1000 and 1250 Oe at the constant magnetizing frequency of 25 Hz and four different values of magnetizing frequency 10, 20, 30 and 40 Hz at a constant magnetic field intensity of 800 Oe were used as MBN analysis parameters. It was found that MBN response depends upon the magnetic field intensity and magnetizing frequency as well on grain size and microhardness of different regions.

Detection of surface cracks in ferromagnetic materials by C-scan mapping of residual stresses using Barkhausen emissions

Surface cracks can develop in components due to residual stresses, fatigue, stress corrosion cracking, corrosion fatigue, etc, during service exposure. Different non-destructive testing (NDT) methods are employed to detect and monitor such cracks. Magnetic Barkhausen Noise (MBN) analysis is one such technique that is used for in situ examination of microstructural anomalies or stress patterns. In the present work, we study the applicability of MBN for the detection of surface cracks. A part through surface crack was created by controlled fatigue loading of a martensitic stainless steel plate. The surface of the sample was scanned for BN emissions in incremental steps parallel and perpendicular to the crack. Measurements of MBN signal strength were recorded and assessed. Localized peaks in the MBN values observed whilst scanning sample surface can reveal the presence of flaws. Furthermore, the remnant stress pattern ahead of the crack tip as well as in the wake of the crack can get reflected in the measured MBN values. The observations carried out show that the surface scan carried out with MBN measurements can be a good non-destructive method for in situ NDT to detect and characterize surface cracks.

Metamagnetic properties in Mn0.7Mg0.3Fe2O4 ferrite

The paper deals with metamagnetic behaviour of the MnMg ferrites with stoichiometric composition Mn0.7Mg0.3Fe2O4 and is focused to structural nature of found effects. The results are a part of the materials research concerning the relationship between the types of the change from antiferomagnetic (AFM) state to ferrimagnetic (FM) state under the influence of temperature at selected magnetic field. In lower applied field under the critical value of strength Hac the increase in magnetic induction B with temperature is attributed to transition from Yafet-Kittel model to Néel's two-sublattices one. Various evaluation methods, such as e.g. thermo-magnetic analysis, magnetic Barkhausen noise analysis, and X-ray diffraction were used for obtaining experimental data. Magnetic Barkhausen noise analysis showed that mainly the domain-wall motion processes take place in the examined MnMg system.

Non-oriented electrical steel with core losses comparable to grain-oriented electrical steel

Abstract A 3.2 wt% Si non-oriented electrical steel (NOES) was processed using conventional rolling and annealing routes, i.e. hot rolling, hot band annealing, cold rolling, and final annealing. The evolution of texture during all the thermomechanical processing stages was investigated using electron backscatter diffraction (EBSD) techniques. It was found that the final annealing temperature and holding time had a profound effect on the texture. At higher temperatures and shorter holding times, the desired 〈1 0 0〉//ND (normal direction) texture was promoted, while the magnetically unfavorable 〈1 1 1〉//ND texture was weakened. The magnetic properties of the steel sheets were measured by Epstein frame method and magnetic Barkhausen noise (MBN) analysis, and it was found that the AC (alternating current) core losses of the NOES annealed at 850 °C for 60 min were comparable to grain-oriented electrical steel (GOES) with the same silicon content and the same sheet thickness, even in the rolling direction (RD). The DC (direct current) core losses and the MBN decreased with increasing grain size, due to the decrease of the pinning sites (grain boundaries). The good magnetic properties of the processed NOES were attributed to a combination of an optimized texture and an appropriate grain size, which was, in turn, the result of proper hot band annealing, fast heating during annealing and a good selection of the annealing temperature and holding time.

Microstructural Characterization of Pack Carburized IS-2062 Low Carbon Steel using Magnetic Barkhausen Noise

Abstract In the present experimental work pack carburized low carbon steel (IS-2062) plates were characterized using magnetic barkhausen noise analysis. Low carbon steel samples were pack carburized under different conditions by varying the temperature. BN analysis along with hysteresis loop measurement was carried at different magnetizing frequency and magnetic field strength. Metallographic analysis was also performed to correlate the magnetic barkhausen noise results. Variation in microstructural changes in steel plates upon pack carburizing heat treatment clearly reflect their effect on BN signal and hysteresis loop characteristics such as permeability and coercivity.

Barkhausen noise-based fatigue life prediction of deep drilled AISI 4140

High-strength steels like AISI 4140 are commonly used for high dynamically loaded parts. Increasing demands for lightweight parts with higher performance and efficiency in automotive industry claim improving material properties. An optimised drilling process should enhance the fatigue life of deep-drilled components by the induction of residual stresses in the borehole, without the need for expensive additional processing steps, e.g. autofrettage. Non-destructive testing techniques like magnetic Barkhausen noise analysis offer quick and reliable possibilities to detect and classify material parameters like hardness and residual stresses. The aim of this study is to evaluate and extrapolate the resulting fatigue performance of deep drilled round specimens due to drilling parameters at an early stage of fatigue life. It was shown, that the coercive field strength decreases approximately linear with proceeding fatigue damage. The slope of the degradation coefficient is comparable for different surface layer conditions. This leads to the assumption that the variation of the micromagnetic parameters is caused by fatigue-induced microstructural changes. Therefore, a microstructure-based prediction of the fatigue life by means of micromagnetic measurements can be established.

Effect of Annealing Temperature on the Texture and Magnetic Barkhausen Noise of a Non-oriented Electrical Steel (0.88 wt% Si) after Inclined Cold Rolling

Inclined cold rolling was employed in this study to process a 0.88 wt% Si non-oriented electrical steel. After conventional hot rolling and annealing, the steel was cold rolled at various angles (i.e. 0°, 45°, and 90°) to the hot rolling direction (HRD), and the cold-rolled steel sheets were then annealed at different temperatures from 600°C to 750°C for 30 seconds to investigate the effect of annealing temperature on the texture and magnetic response of the material. The texture was measured by electron backscatter diffraction (EBSD), and the magnetic response of the steel was evaluated by magnetic Barkhausen noise (MBN) analysis. It was found that all the cold-rolled steels partially recrystallize at temperatures below 750°C, but the progress of recrystallization differs in steels cold rolled at different angles to the HRD, i.e. samples rolled at 45° to the HRD recrystallize faster than those after conventional rolling (0° to HRD) or cross rolling (90° to the HRD). The initial cold rolling texture (mainly the α-fibre and γ-fibre) may change to cube, rotated cube, rotated Goss or {111}<112> depending on the rolling scheme and the annealing temperature. The MBN root mean square values of the samples cold rolled at different angles to the HRD show substantial differences during the annealing process. At low annealing temperatures (600°C and 650°C), the anisotropy of MBN in the conventionally rolled steel is much higher than those after inclined rolling or cross rolling.

Induction Hardened Layer Characterization and Grinding Burn Detection by Magnetic Barkhausen Noise Analysis

The quality of the ball screw shafts used in the aeronautical sector has to be controlled and certified with the most advanced non-destructive techniques. The capacity of magnetic Barkhausen noise (MBN) as a non-destructive technique to control the quality of ball screw shafts by assuring the appropriate induction hardened layer depth and detecting local overheated regions, known as grinding burns, which may occur during grinding processes is shown in the present work. Magnetic Barkhausen noise measurements were made with a system designed and implemented by the authors and the derived parameters were compared with microhardness measurements made at various depths after the different induction hardening treatments and the grinding processes were applied. A multiparametric study of the MBN signal as a function of the magnetic field in the surface of the sample is done in order to estimate the thickness of the hardened layer and to detect the grinding burns produced during grinding processes. The hardened layer thickness can be characterized with an error of ±200 \(\upmu \)m in the range between 150 and 2500 \(\upmu \)m by the position of the first peak of the MBN envelope in terms of the tangential magnetic field measured at the surface and the grinding burns can be detected with the position of the second peak of the MBN envelope in terms of the tangential magnetic field measured at the surface.

Application of micro-magnetic testing systems for non-destructive analysis of wear progress in case-hardened 16MnCr5 gear wheels

Abstract Micro-magnetic testing methods are qualified for non-destructive quantification of hardness, hardness depth and residual stresses. Among others they are applied for detection of grinding burn in gear wheels, but an application for wear condition monitoring has not yet been published. In this paper, results of initial research of determination of wear condition in gear wheels by application of micro-magnetic testing systems are presented. For comparison of different wear conditions, gears were loaded for increasing numbers of cycles in a test rig based on FVA information sheet 54/7 and DIN ISO 14635 part 1. Operating conditions were altered by usage of different lubricants. Afterwards, wear conditions were determined by conventional techniques, i. e., measuring change in profile and loss of material. Four measurement principles were evaluated for change in micro-magnetic properties determination, magnetic Barkhausen noise analysis, permeability and eddy-current measurements, as well as harmonic analysis of tangential field strength. A general suitability of micro-magnetic testing approach for characterization of wear condition of gear wheels could be demonstrated by comparison of micro-magnetic properties with common wear indicators. Micro-magnetic properties were not solely influenced by wear condition, as the selected oil, and hence the tribochemical conditions in contact also showed a significant effect on measured values. Therefore, further survey is required for direct correlation of micro-magnetic properties with (micro-)structural material changes.