Statistical evaluation of Barkhausen noise testing (BNT) for ground samples
|Author:||Tomkowski, Robert1; Sorsa, Aki2; Santa-aho, Suvi3;|
1Manufacturing and Metrology Systems, Department of Production Engineering, School of Industrial Engineering and Management, KTH Royal Institute of Technology, Brinellvägen 68, 114 28 Stockholm, Sweden
2Control Engineering, Environmental and Chemical Engineering, Faculty of Technology, University of Oulu, P.O. Box 4300, FI-90014 Oulu, Finland
3Faculty of Engineering and Natural Sciences, Tampere University, P.O. Box 589, FI-33014 Tampere, Finland
4Schlumpf Scandinavia AB, Flygfältsgatan 2D, 128 30 Skarpnäck, Sweden
|Online Access:||PDF Full Text (PDF, 3.8 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202001152220
Multidisciplinary Digital Publishing Institute,
|Publish Date:|| 2020-01-15
Barkhausen noise testing (BNT) is a nondestructive method for investigating many properties of ferromagnetic materials. The most common application is the monitoring of grinding burns caused by introducing locally high temperatures while grinding. Other features, such as microstructure, residual stress changes, hardening depth, and so forth, can be monitored as well. Nevertheless, because BNT is a method based on a complex magnetoelectric phenomenon, it is not yet standardized. Therefore, there is a need to study the traceability and stability of the measurement method. This study aimed to carry out a statistical analysis of ferromagnetic samples after grinding processes by the use of BNT. The first part of the experiment was to grind samples in different facilities (Sweden and Finland) with similar grinding parameters, different grinding wheels, and different hardness values. The second part was to evaluate measured BNT parameters to determine significant factors affecting BNT signal value. The measurement data from the samples were divided into two different batches according to where they were manufactured. Both grinding batches contained measurement data from three different participants. The main feature for calculation was the root-mean-square (RMS) value. The first processing step was to normalize the RMS values for all the measurements. A standard analysis of variance (ANOVA) was applied for the normalized dataset. The ANOVA showed that the grinding parameters had a significant impact on the BNT signal value, while the other investigated factors (e.g., participant) were negligible. The reasons for this are discussed at the end of the paper.
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
216 Materials engineering
This research was funded by VINNOVA, grant number 2015-03721, and the Academy of Finland, grant number 288842.
|Academy of Finland Grant Number:||
288842 (Academy of Finland Funding decision)
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).