New feature extraction for applied stress detection on ferromagnetic material using magnetic Barkhausen noise

Measurement ◽  
2015 ◽  
Vol 73 ◽  
pp. 515-519 ◽  
Author(s):  
Song Ding ◽  
GuiYun Tian ◽  
V. Moorthy ◽  
Ping Wang
Keyword(s):  
Feature Extraction ◽  
Applied Stress ◽  
Ferromagnetic Material ◽  
Barkhausen Noise ◽  
Stress Detection ◽  
Magnetic Barkhausen Noise ◽  
New Feature

scholarly journals Time-Response-Histogram-Based Feature of Magnetic Barkhausen Noise for Material Characterization Considering Influences of Grain and Grain Boundary under In Situ Tensile Test

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2350
Author(s):  
Jia Liu ◽  
Guiyun Tian ◽  
Bin Gao ◽  
Kun Zeng ◽  
Yongbing Xu ◽  
...  
Keyword(s):  
Grain Boundary ◽  
Tensile Stress ◽  
Material Properties ◽  
Ferromagnetic Material ◽  
Silicon Steel ◽  
Time Response ◽  
Barkhausen Noise ◽  
Time Interval ◽  
Magnetic Barkhausen Noise

Stress is the crucial factor of ferromagnetic material failure origin. However, the nondestructive test methods to analyze the ferromagnetic material properties’ inhomogeneity on the microscopic scale with stress have not been obtained so far. In this study, magnetic Barkhausen noise (MBN) signals on different silicon steel sheet locations under in situ tensile tests were detected by a high-spatial-resolution magnetic probe. The domain-wall (DW) motion, grain, and grain boundary were detected using a magneto-optical Kerr (MOKE) image. The time characteristic of DW motion and MBN signals on different locations was varied during elastic deformation. Therefore, a time-response histogram is proposed in this work to show different DW motions inside the grain and around the grain boundary under low tensile stress. In order to separate the variation of magnetic properties affected by the grain and grain boundary under low tensile stress corresponding to MBN excitation, time-division was carried out to extract the root-mean-square (RMS), mean, and peak in the optimized time interval. The time-response histogram of MBN evaluated the silicon steel sheet’s inhomogeneous material properties, and provided a theoretical and experimental reference for ferromagnetic material properties under stress.

Influence of Defects on Stress Detection by Magnetic Barkhausen Noise

2021 ◽  
Vol 40 (4) ◽  
Author(s):  
Hongming Tu ◽  
Jianbo Wu ◽  
Maciej Roskosz ◽  
Chengyong Liu ◽  
Shicheng Qiu
Keyword(s):  
Barkhausen Noise ◽  
Stress Detection ◽  
Magnetic Barkhausen Noise

Motion-Induced Magnetic Barkhausen Noise for Evaluating Applied Stress in Pipelines

2020 ◽  
Vol 39 (4) ◽  
Author(s):  
Jianbo Wu ◽  
Chengyong Liu ◽  
Erlong Li ◽  
Junzhen Zhu ◽  
Song Ding ◽  
...  
Keyword(s):  
Applied Stress ◽  
Barkhausen Noise ◽  
Magnetic Barkhausen Noise

scholarly journals A Method of Barkhausen Noise Feature Extraction Based on an Adaptive Threshold

2019 ◽  
Vol 9 (15) ◽  
pp. 2964 ◽  
Author(s):  
Hang ◽  
Liu ◽  
Wang
Keyword(s):  
Feature Extraction ◽  
Maximum Amplitude ◽  
Adaptive Threshold ◽  
Barkhausen Noise ◽  
New Approach ◽  
Feature Extraction Method ◽  
Modelling Techniques ◽  
New Feature ◽  
Low Dispersion ◽  
Pulse Count

This paper reports on a new feature extraction method for detection of applied stress using magnetic Barkhausen noise (MBN). Some previous methods for extracting MBN features need to choose a suitable threshold so that these features can have good linearity and low dispersion, such as pulse count and full width at 25, 50 and 75% of the maximum amplitude. A new approach has been proposed for selecting the appropriate threshold for MBN features adaptively using a genetic algorithm (GA). The criterion for selecting the threshold is the lowest standard deviation of features and new proposed ‘overlap’ of features. In order to verify the effectiveness of the adaptive pulse count feature for stress detection, different modelling techniques are compared, including multivariable linear regression (MLR) and multilayer perceptron (MLP). The results obtained have proven that adaptive threshold features can effectively distinguish between different stress conditions compared with traditional MBN features.

scholarly journals Research on Stress Detection of DC01 Steel via Barkhausen Noise

2020 ◽  
Author(s):  
Xiang Zhang ◽  
Jianping Peng ◽  
Xiaorong Gao ◽  
Jie Bai ◽  
Jianqiang Guo
Keyword(s):  
Tensile Stress ◽  
Applied Stress ◽  
Convenient Method ◽  
Magnetic Domain ◽  
Point Of View ◽  
Downward Trend ◽  
Barkhausen Noise ◽  
Stress Detection ◽  
Energy Point ◽  
Magnetic Strength

The industrial component under loading change its mechanical characteristics by stress. It is very important to make clear the distribution of the applied stress in the component to reduce the failure. In this paper, magnetic Barkhausen noise (MBN) method is used to evaluate the stress of DC01 steel. Combined with theory for both magnetic domain and magnetization, this work analyzed MBN signal from energy point of view. Magnetic strength corresponding to the maximum MBN shows a downward trend with the increase of tensile stress. Plots of energy against stress showed a relationship providing a convenient method for detecting stress levels by MBN.

Research on pipeline internal stress detection technology based on the Barkhausen effect

2020 ◽  
Vol 62 (9) ◽  
pp. 550-554
Author(s):  
YiLai Ma ◽  
JinZhong Chen ◽  
RenBi He ◽  
Tao Meng ◽  
RenYang He
Keyword(s):  
Stress Concentration ◽  
Oil And Gas ◽  
Operating Conditions ◽  
Barkhausen Noise ◽  
Stress Detection ◽  
Magnetic Barkhausen Noise ◽  
Barkhausen Effect ◽  
Long Distance ◽  
Optimal Position ◽  
Detection Technology

Focusing on the requirements of pipeline in-line testing for stress concentration, mechanical scratches and corrosion discrimination, a numerical calculation and experimental verification study of the internal testing excitation of oil and gas pipelines based on the Barkhausen effect (magnetic Barkhausen noise (MBN)) is carried out. This paper uses finite element calculation to determine the optimal position of the sensor, quantitatively analyses the influence of parameters, such as the excitation structure size and excitation intensity, on the magnetisation field of the pipeline and obtains the optimal exciting parameters for acquiring continuous Barkhausen signals, which can provide references for designing the pipeline in-line inspection gauge for stress concentration. The feasibility of the continuous Barkhausen noise (CBN) method for long-distance pipeline stress detection is verified by simulating the operating conditions of the internal detector in the pipeline using dynamic rotating excitation.

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