Non-destructive scanning for applied stress by the continuous magnetic Barkhausen noise method

Grijalba, Freddy Armando Franco; Padovese, Linilson Rodrigues

doi:10.1016/j.jmmm.2017.09.036

Cited by 16 publications

(9 citation statements)

References 24 publications

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“…Caldas-Morgan et al [45] noticed that the BN generation was less noticeable at lower speeds. The same effect was noticed by Franco Grijalba et al [46]. However, during scanning, the probe needs to be kept still for at least half of a magnetization cycle [9].…”

Section: Continuous Magnetic Barkhausen Noise (Cmbn)supporting

confidence: 67%

“…However, during scanning, the probe needs to be kept still for at least half of a magnetization cycle [9]. The CMBN measurement method is a relative technique and requires a calibration procedure [46].…”

Section: Continuous Magnetic Barkhausen Noise (Cmbn)mentioning

confidence: 99%

“…In order to obtain usable results from simulations, a great deal of pre-existing information about the magnetizing [46] parameters of the BN probe is required. In the FEM software ANSYS, the coil is modelled as a uniform density load domain with a value of A/m 2 .…”

Section: Utilization Of Finite Element Modelling In Barkhausen Noise mentioning

confidence: 99%

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Barkhausen Noise Probes and Modelling: A Review

et al. 2019

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This review looks at the main types of magnetic Barkhausen noise (BN) probes that have been developed. The aim of this review is to summarize the existing knowledge of magnetic Barkhausen noise probes and the magnetic modelling of them. The BN probes have been the focus of many previous studies, but no sufficient review or conclusions have been made so far. This review focuses on combining information regarding the different types of BN probes and their modelling. The review is divided into two sections; in the first part the different designs and types of Barkhausen noise probes are introduced. The second part of the review deals with the BN probe modelling with various modelling software. Finally, a comparison of the experimental measurements is made and BN sensitivity is discussed.

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Section: Continuous Magnetic Barkhausen Noise (Cmbn)supporting

confidence: 67%

Section: Continuous Magnetic Barkhausen Noise (Cmbn)mentioning

confidence: 99%

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Barkhausen Noise Probes and Modelling: A Review

et al. 2019

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“…Consequently, these obstacles arising in the material require additional energy and cause discontinuous changes of the magnetic state. This phenomenon has been studied and gradually used for non-destructive testing (NDT) of materials [4,5,6,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33]. The stepwise change of the magnetization level during operation of the alternating magnetizing field can be observed by coil placed in the neighbourhood of the material.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, a voltage U BN called the Barkhausen Noise (BN) is induced in coil. The Magnetic Barkhausen Noise method (MBN) is used mainly for [29]: detection and evaluation of fatigue and stress [4,5,6,11,12,16,17,22,24,26,31,32,34,35,36,37,38,39], material microstructure [19,20,28,37,38,40] and microhardness (i.e., hardening level, case depth) analysis [13,14,23,27].…”

Section: Introductionmentioning

confidence: 99%

Use of Time-Dependent Multispectral Representation of Magnetic Barkhausen Noise Signals for the Needs of Non-Destructive Evaluation of Steel Materials

Maciusowicz

Psuj

2019

Sensors

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Due to the existing relationship between microstructural properties and magnetic ones of the ferromagnetic materials, the application potential of the magnetic Barkhausen noise (BN) method to non-destructive testing is constantly growing. However, the stochastic nature of the Barkhausen effect requires the use of advanced signal processing methods. Recently, the need to apply time-frequency (TF) transformations to the processing of BN signals arose. However, various TF methods have been used in the majority of cases for qualitative signal conditioning and no extensive analysis of TF-based information has been conducted so far. Therefore, in this paper, the wide analysis of BN TF representation was carried out. Considering the properties of TF transformations, the Short-Time Fourier Transform (STFT) was used. A procedure for definition of the envelopes of the TF characteristic was proposed. To verify the quality of extracted features, an analysis was performed on the basis of BN signals acquired during stress loading experiments of steel elements. First, the preliminary experiments were processed for various parameters of the measuring system and calculation procedures. The feature extraction procedure was performed for different modes of TF representations. Finally, the distributions of TF features over the loading stages are presented and their information content was validated using commonly used features derived from time T and frequency F domains.

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