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Statistical evaluation of barkhausen noise testing (BNT) for ground samples

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Statistical evaluation of barkhausen noise testing (BNT) for ground samples. / Tomkowski, Robert; Sorsa, Aki; Santa-Aho, Suvi; Lundin, Per; Vippola, Minnamari.

julkaisussa: Sensors (Switzerland), Vuosikerta 19, Nro 21, 4716, 01.11.2019.

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Tomkowski, R, Sorsa, A, Santa-Aho, S, Lundin, P & Vippola, M 2019, 'Statistical evaluation of barkhausen noise testing (BNT) for ground samples', Sensors (Switzerland), Vuosikerta. 19, Nro 21, 4716. https://doi.org/10.3390/s19214716

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Tomkowski, Robert ; Sorsa, Aki ; Santa-Aho, Suvi ; Lundin, Per ; Vippola, Minnamari. / Statistical evaluation of barkhausen noise testing (BNT) for ground samples. Julkaisussa: Sensors (Switzerland). 2019 ; Vuosikerta 19, Nro 21.

Bibtex - Lataa

@article{d522c967a5ff4c4e9bf0c26431683d90,
title = "Statistical evaluation of barkhausen noise testing (BNT) for ground samples",
abstract = "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.",
keywords = "ANOVA, Barkhausen noise testing (BNT), Proficiency test, Uncertainty",
author = "Robert Tomkowski and Aki Sorsa and Suvi Santa-Aho and Per Lundin and Minnamari Vippola",
year = "2019",
month = "11",
day = "1",
doi = "10.3390/s19214716",
language = "English",
volume = "19",
journal = "Sensors",
issn = "1424-8220",
publisher = "MDPI",
number = "21",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Statistical evaluation of barkhausen noise testing (BNT) for ground samples

AU - Tomkowski, Robert

AU - Sorsa, Aki

AU - Santa-Aho, Suvi

AU - Lundin, Per

AU - Vippola, Minnamari

PY - 2019/11/1

Y1 - 2019/11/1

N2 - 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.

AB - 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.

KW - ANOVA

KW - Barkhausen noise testing (BNT)

KW - Proficiency test

KW - Uncertainty

U2 - 10.3390/s19214716

DO - 10.3390/s19214716

M3 - Article

VL - 19

JO - Sensors

JF - Sensors

SN - 1424-8220

IS - 21

M1 - 4716

ER -