Magnetic Barkhausen Noise Emission: Surface Integrity

Author(s):  
Janez Grum
2018 ◽  
Vol 18 (6) ◽  
pp. 962-966
Author(s):  
Anna Mičietová ◽  
Juraj Uríček ◽  
Daniel Heim ◽  
Mária Čilliková ◽  
Miroslav Neslušan

2020 ◽  
Vol 87 (12) ◽  
pp. 787-798
Author(s):  
Rahel Jedamski ◽  
Jonas Heinzel ◽  
Maximilian Rößler ◽  
Jérémy Epp ◽  
Jochen Eckebrecht ◽  
...  

AbstractGrinding 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.


Author(s):  
Martin Unterberg ◽  
Joachim Stanke ◽  
Daniel Trauth ◽  
Thomas Bergs

AbstractThe process setup of manufacturing processes is generally knowledge-based and carried out once for a material batch. Industry experts observe fluctuations in product quality and tool life, albeit the process setup remains unchanged. These fluctuations are mainly attributed to fluctuations in material parameters. An in-situ detection of changes in material parameters would enable manufacturers to adapt process parameters like forces or lubrication before turbulences like unexpectedly high tool wear or degradation in product quality occurs. This contribution shows the applicability of a deep learning time series classification architecture that does not rely on handcrafted feature engineering for the classification of hardness fluctuations in a sheet-metal coil using magnetic Barkhausen noise emission. This methodology is not limited to the detection of hardness fluctuations in sheet-metal coils and can potentially be applied for the in-situ material property classification in different manufacturing processes and for different material parameters.


2021 ◽  
Vol 40 (3) ◽  
Author(s):  
M. Jančula ◽  
M. Neslušan ◽  
F. Pastorek ◽  
M. Pitoňák ◽  
V. Pata ◽  
...  

2018 ◽  
Vol 244 ◽  
pp. 02002
Author(s):  
Mária Čilliková ◽  
Miroslav Neslušan ◽  
Anna Mičietová ◽  
Juraj Uríček

This paper deals with surface integrity after hard milling of high tempered bearing steel 100Cr6. Surface integrity is expressed in terms of shape deviation as well as Barkhausen noise emission. Furthermore, components of cutting forces are also measured as a function of tool wear and their non homogenity within the contact between the milling cutter and workpiece is discussed. The results of measurements indicate that shape as well as structure remarkable non homogeneity should expected after hard milling due to missing full contact between milling cutter and workpiece. This non homogeneity can be monitored via Barkhausen noise technique. On the other hand the competitive grinding cycles produced more homogenous surface and surface state is a function of infeed speed.


Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2350
Author(s):  
Jia Liu ◽  
Guiyun Tian ◽  
Bin Gao ◽  
Kun Zeng ◽  
Yongbing Xu ◽  
...  

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.


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