Schadenserfassung auf Radsatzlaufflächen/Defect detection on wheelset treads – Measurement of Magnetic Barkhausen Noise to detect varying workpiece conditions

2019 ◽  
Vol 109 (11-12) ◽  
pp. 811-815
Author(s):  
B. Denkena ◽  
B. Bergmann ◽  
H. Blech
Keyword(s):  
Acoustic Emission ◽  
Process Parameters ◽  
Defect Detection ◽  
Material Properties ◽  
Barkhausen Noise ◽  
Magnetic Barkhausen Noise ◽  
Optimal Process ◽  
Process Reliability

Unterschiedliche Belastungshistorien von Eisenbahnrädern führen zu Werkstoffveränderungen in der Lauffläche. Diese verursachen sporadisches Werkzeugversagen und verringern so die Prozesssicherheit. Die Messung der Material- und Prozesseigenschaften mit Barkhausenrauschen und Körperschall erlauben, individuelle Bearbeitungsparameter für jedes Exemplar festzulegen. Gezeigt werden die Herausforderungen in der Radsatzbearbeitung, und welche Informationen sich durch die Messtechniken gewinnen lassen.   Different load histories of train wheels lead to high variance of material properties on the running tread. Those cause unpredictable tool break and reduce process reliability. The measurement of magnetic Barkhausen noise and acoustic emission allow to gain information of the workpiece and the running process, to find optimal process parameters for the reconditioning of every individual wheel. Typical issues in train wheel machining and results of measurements are presented.

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.

Magnetic Barkhausen noise and magneto acoustic emission in pressure vessel steel

2017 ◽  
Vol 426 ◽  
pp. 779-784 ◽  
Author(s):  
Miriam Rocío Neyra Astudillo ◽  
María Isabel López Pumarega ◽  
Nicolás Marcelo Núñez ◽  
Alberto Pochettino ◽  
José Ruzzante
Keyword(s):  
Acoustic Emission ◽  
Pressure Vessel ◽  
Barkhausen Noise ◽  
Pressure Vessel Steel ◽  
Magnetic Barkhausen Noise ◽  
Vessel Steel

scholarly journals Magnetic Barkhausen Noise and Magneto Acoustic Emission in Stainless Steel Plates

2015 ◽  
Vol 8 ◽  
pp. 674-682 ◽  
Author(s):  
Neyra Astudillo Miriam Rocío ◽  
Núñez Nicolás ◽  
López Pumarega María Isabel ◽  
Ruzzante José ◽  
Padovese Linilson
Keyword(s):  
Stainless Steel ◽  
Acoustic Emission ◽  
Steel Plates ◽  
Barkhausen Noise ◽  
Magnetic Barkhausen Noise

scholarly journals A FEM-Based 2D Model for Simulation and Qualitative Assessment of Shot-Peening Processes

Materials ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 2784
Author(s):  
Georgios Maliaris ◽  
Christos Gakias ◽  
Michail Malikoutsakis ◽  
Georgios Savaidis
Keyword(s):  
Process Parameters ◽  
Material Properties ◽  
Shot Peening ◽  
Qualitative Assessment ◽  
Experimental Investigations ◽  
Elastoplastic Material ◽  
Size Distributions ◽  
User Friendly ◽  
The Impact ◽  
2D Model

Shot peening is one of the most favored surface treatment processes mostly applied on large-scale engineering components to enhance their fatigue performance. Due to the stochastic nature and the mutual interactions of process parameters and the partially contradictory effects caused on the component’s surface (increase in residual stress, work-hardening, and increase in roughness), there is demand for capable and user-friendly simulation models to support the responsible engineers in developing optimal shot-peening processes. The present paper contains a user-friendly Finite Element Method-based 2D model covering all major process parameters. Its novelty and scientific breakthrough lie in its capability to consider various size distributions and elastoplastic material properties of the shots. Therewith, the model is capable to provide insight into the influence of every individual process parameter and their interactions. Despite certain restrictions arising from its 2D nature, the model can be accurately applied for qualitative or comparative studies and processes’ assessments to select the most promising one(s) for the further experimental investigations. The model is applied to a high-strength steel grade used for automotive leaf springs considering real shot size distributions. The results reveal that the increase in shot velocity and the impact angle increase the extent of the residual stresses but also the surface roughness. The usage of elastoplastic material properties for the shots has been proved crucial to obtain physically reasonable results regarding the component’s behavior.

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