Statistical Evaluation of Barkhausen Noise Testing (BNT) for Ground Samples.

ANOVA Barkhausen noise testing (BNT) proficiency test uncertainty

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
30 Oct 2019
Historique:
received: 03 10 2019
revised: 22 10 2019
accepted: 28 10 2019
entrez: 2 11 2019
pubmed: 2 11 2019
medline: 2 11 2019
Statut: epublish

Résumé

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.

Identifiants

pubmed: 31671620
pii: s19214716
doi: 10.3390/s19214716
pmc: PMC6864872
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Robert Tomkowski (R)

Manufacturing and Metrology Systems, Department of Production Engineering, School of Industrial Engineering and Management, KTH Royal Institute of Technology, Brinellvägen 68, 114 28 Stockholm, Sweden. rtom@kth.se.

Aki Sorsa (A)

Control Engineering, Environmental and Chemical Engineering, Faculty of Technology, University of Oulu, P.O. Box 4300, FI-90014 Oulu, Finland. aki.sorsa@oulu.fi.

Suvi Santa-Aho (S)

Faculty of Engineering and Natural Sciences, Tampere University, P.O. Box 589, FI-33014 Tampere, Finland. suvi.santa-aho@tuni.fi.

Per Lundin (P)

Schlumpf Scandinavia AB, Flygfältsgatan 2D, 128 30 Skarpnäck, Sweden. per.lundin@schlumpf.se.

Minnamari Vippola (M)

Faculty of Engineering and Natural Sciences, Tampere University, P.O. Box 589, FI-33014 Tampere, Finland. minnamari.vippola@tuni.fi.

Classifications MeSH