Toggle Main Menu Toggle Search

Open Access padlockePrints

The Newcastle University research output collection, currently available on ePrints, will shortly be moving to a new open repository platform, Figshare. To prepare for the data migration we have paused adding new content to ePrints, and will resume once the new repository is launched. During this time you will continue to have access to ePrints (but no new content will appear). We will share updates here when available.

Analysis of domain wall dynamics based on skewness of magnetic Barkhausen noise for applied stress determination

Lookup NU author(s): Song Ding, Professor Gui Yun TianORCiD

Downloads


Licence

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

© 2016 Elsevier B.V. Skewness of Magnetic Barkhausen Noise (MBN) signal is used as a new feature for applied stress determination. After experimental studies, skewness presents its ability for measuring applied tensile stress compared with conventional feature, meanwhile, a non-linear behavior of this new feature and an independence of the excitation conditions under compressive stress are found and discussed. Effective damping during domain wall motion influencing the asymmetric shape of the MBN statistical distribution function is discussed under compressive and tensile stress variation. Domain wall (DW) energy and distance between pinning edges of the DW are considered altering the characteristic relaxation time, which is the reason for the non-linear phenomenon of skewness.


Publication metadata

Author(s): Ding S, Tian G, Dobmann G, Wang P

Publication type: Article

Publication status: Published

Journal: Journal of Magnetism and Magnetic Materials

Year: 2017

Volume: 421

Pages: 225-229

Print publication date: 01/01/2017

Online publication date: 08/08/2016

Acceptance date: 08/08/2016

Date deposited: 13/12/2017

ISSN (print): 0304-8853

Publisher: Elsevier B.V.

URL: https://doi.org/10.1016/j.jmmm.2016.08.030

DOI: 10.1016/j.jmmm.2016.08.030


Altmetrics

Altmetrics provided by Altmetric


Share