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

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
Control Engineering, Environmental and Chemical Engineering, Faculty of Technology, University of Oulu, P.O. Box 4300, FI-90014 Oulu, Finland
Faculty of Engineering and Natural Sciences, Tampere University, P.O. Box 589, FI-33014 Tampere, Finland
Schlumpf Scandinavia AB, Flygfältsgatan 2D, 128 30 Skarpnäck, Sweden
Authors to whom correspondence should be addressed.
Received: 3 October 2019 / Revised: 22 October 2019 / Accepted: 28 October 2019 / Published: 30 October 2019
(This article belongs to the Section Physical Sensors)
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. View Full-Text
Keywords: Barkhausen noise testing (BNT); uncertainty; proficiency test; ANOVA Barkhausen noise testing (BNT); uncertainty; proficiency test; ANOVA
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MDPI and ACS Style

Tomkowski, R.; Sorsa, A.; Santa-aho, S.; Lundin, P.; Vippola, M. Statistical Evaluation of Barkhausen Noise Testing (BNT) for Ground Samples. Sensors 2019, 19, 4716.

AMA Style

Tomkowski R, Sorsa A, Santa-aho S, Lundin P, Vippola M. Statistical Evaluation of Barkhausen Noise Testing (BNT) for Ground Samples. Sensors. 2019; 19(21):4716.

Chicago/Turabian Style

Tomkowski, Robert, Aki Sorsa, Suvi Santa-aho, Per Lundin, and Minnamari Vippola. 2019. "Statistical Evaluation of Barkhausen Noise Testing (BNT) for Ground Samples" Sensors 19, no. 21: 4716.

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