Evaluation of applied and residual stresses in case-carburised En36 steel subjected to bending using the magnetic Barkhausen emission technique

Moorthy, V. K.; Shaw, Brian; Day, S D

doi:10.1016/j.actamat.2003.12.034

Cited by 29 publications

(12 citation statements)

References 14 publications

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“…Final published version of this paper is available at http://dx.doi.org/10.1016/j.jmmm.2013.06.038 With yoke Y2, the maximum applied magnetic field strength is sufficient enough to induce strong magnetisation of hard near-surface region to generate MBN peak 2 at higher excitation voltage. Such two-peak MBN profiles have been observed earlier in case hardened steels [15,16]. In case of carburised steel, the peak 1 at lower field is attributed to the movement of domains walls in softer region in the subsurface (>300 µm depth) and the peak 2 at higher field is attributed to the movement of domains walls in the harder region near the surface (<300 µm depth) [16].…”

Section: Mbn Profiles For Different Pick-up Coilssupporting

confidence: 74%

Influence of applied magnetic field strength and frequency response of pick-up coil on the magnetic barkhausen noise profile

Vashista

Moorthy

2013

Journal of Magnetism and Magnetic Materials

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The influence of applied magnetic field strength and frequency response of the pickup coil on the shape of Magnetic Barkhausen Noise (MBN) profile have been studied. The low frequency MBN measurements have been carried out using 5 different MBN pickup coils at two different ranges of applied magnetic field strengths on quenched & tempered (QT) and case-carburised & tempered (CT) 18CrNiMo7 steel bar samples. The MBN pickup coils have been designed to obtain different frequency response such that the peak frequency response varies from ~ 4 kHz to ~32 kHz and the amplitude of low frequency signals decreases gradually. At lower applied magnetic field strength of ±14000 A/m, all the pickup coils produced a single peak MBN profile for both QT and CT sample. However, at higher applied magnetic field strength of ±22000 A/m, the MBN profile showed two peaks for both QT and CT samples for pickup coils with peak frequency response up to ~17 kHz. Also, there is systematic reduction in peak 2 for QT sample and asymmetric reduction in the heights of peak 1 and peak 2 for CT sample with increase in peak frequency response of the pickup coils. The decreasing sensitivity of pickup coils with increasing peak frequency response to MBN signal generation is indicated by the gradual reduction in width of MBN profile and height of peak 2 in QT sample. The drastic reduction in peak 1 as compared to peak 2 in CT sample shows the effect of decreasing low frequency response of the pickup coils on lowering skindepth of MBN signal detection. This study clearly suggests that it is essential to optimise both maximum applied magnetic field strength and frequency response of the MBN pickup coil for maximising the shape of the MBN profile for appropriate correlation with the magnetisation process and hence the material properties.

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Section: Mbn Profiles For Different Pick-up Coilssupporting

confidence: 74%

Influence of applied magnetic field strength and frequency response of pick-up coil on the magnetic barkhausen noise profile

Vashista

Moorthy

2013

Journal of Magnetism and Magnetic Materials

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“…In the literature, the overall amount of Barkhausen activity (the RMS value and the BN energy) has been shown to increase with increasing tensile stress and decrease with increasing compressive stress (9,10,17) . Thus, the sign of the coefficient b 4 in Table 5 should be positive.…”

Section: The Selected Featuresmentioning

confidence: 97%

“…It is shown in the literature that these computational features can be used in estimating the properties of the materials. For example, the features corresponding to Barkhausen activity (such as the RMS value and the BN energy) have been shown to increase with increasing tensile stress and decrease with increasing compressive stress (9,10,17) . Also, the shape and position of the profile is influenced by the stresses, as shown in (10,(18)(19)(20) .…”

Section: Introductionmentioning

confidence: 97%

“…The BN energy is obtained by integrating the squared noise signal over one BN envelope (16) . Another approach is to consider the sliding RMS value of the signal as a function of the applied magnetic field (3)(4)(5)9,10) . Thus, the so-called BN profile is obtained, which can be used to determine features such as peak height, position and width (5,10,15) .…”

Section: Introductionmentioning

confidence: 99%

“…According to the literature, BN can be used in evaluating, for example, the microstructure (2)(3)(4)(5) , stress state (5)(6)(7)(8)(9)(10) , fatigue (11)(12)(13) and hardness (14,15) of the material. A typical approach is to calculate either the RMS value (1,2,14) or the BN energy (7,8) of the BN signal and compare the obtained values to the changes in the studied material property.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A data-based modelling scheme for estimating residual stress from Barkhausen noise measurements

Sorsa¹,

Leiviskä²,

Santa-aho³

et al. 2012

Insight

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BARKHAUSENBarkhausen noise measurement is an intriguing technique for the non-destructive testing of material properties. It is applicable to ferromagnetic materials and shown to be sensitive to many material properties. Typically, some features are calculated from the Barkhausen noise signal and compared to the material properties. However, the results are mainly qualitative. In this study, quantitative prediction of residual stress based on the Barkhausen noise measurement is studied. The studied material is case-hardened steel 18CrNiMo7-6 (EN 10084). The development of the prediction model is divided into feature generation and selection, followed by model identification and validation. In feature generation, the aim is to generate features as robust as possible, while in feature selection the most suitable features are selected to be used in the prediction model. In the model identification step, a simple linear regression model is identified. The model is validated in the final modelling step to ensure that it can also be used for future predictions. The identified model gives rather accurate predictions, indicating that the proposed modelling approach is applicable for predicting material properties from the Barkhausen noise signal.

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Magnetoresistance, transport noise and granular structure in polycrystalline superconductors

García-Fornaris

Govea-Alcaide

Muné

et al. 2007

Physica Status Solidi (a)

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In this work we present a theoretical study on the magnetic field dependence of the electrical resistance R (Ba) and the transport noise (TN) in a high‐Tc polycrystalline superconductors. In the model, we have considered the ceramic superconductor as a series‐parallel array of Josephson devices and the intergranular magnetic field is described within the framework of the intragranular flux‐trapping model. The obtained results qualitatively reproduce the hysteretic behavior of the R (Ba) dependence in increasing and decreasing applied magnetic fields. We have found that the hysteretic behavior in the R (Ba) dependence changes appreciably if different statistical distributions of the geometric factors of grains are used. In addition, such changes are also reflected in the TN, which is produced by the electric current rearrangement in the array with increasing applied magnetic fields. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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Evaluation of applied and residual stresses in case-carburised En36 steel subjected to bending using the magnetic Barkhausen emission technique

Cited by 29 publications

References 14 publications

Influence of applied magnetic field strength and frequency response of pick-up coil on the magnetic barkhausen noise profile

Influence of applied magnetic field strength and frequency response of pick-up coil on the magnetic barkhausen noise profile

A data-based modelling scheme for estimating residual stress from Barkhausen noise measurements

Magnetoresistance, transport noise and granular structure in polycrystalline superconductors

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