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Nondestructive Testing and Evaluation Volume 36, 2021 - Issue 5

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Research Article

Case depth evaluation of induction-hardened camshaft by using magnetic Barkhausen noise (MBN) method

P.L. Tama Department of Industrial and Materials Science, Chalmers University of Technology, Gothenburg, SwedenCorrespondence[email protected]
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P. Hammersberga Department of Industrial and Materials Science, Chalmers University of Technology, Gothenburg, SwedenView further author information

G. Perssona Department of Industrial and Materials Science, Chalmers University of Technology, Gothenburg, SwedenView further author information

J. Olavisonb Volvo Group Trucks Operations Powertrain Production, Skövde, SwedenView further author information

Pages 494-514 | Received 18 Oct 2019, Accepted 18 Aug 2020, Published online: 28 Sep 2020

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https://doi.org/10.1080/10589759.2020.1813284
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Citations (3)

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Articles from other publishers (3)

Jonas Holmberg, Peter Hammersberg, Per Lundin & Jari Olavison. (2022) Predictive Modeling of Induction-Hardened Depth Based on the Barkhausen Noise Signal. Micromachines 14:1, pages 97.
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Michal Maciusowicz & Grzegorz Psuj. (2022) Classification of Grain-Oriented Electrical Steel Sheets by Magnetic Barkhausen Noise Using Time-Frequency Analysis and Selected Machine Learning Algorithms. Applied Sciences 12:23, pages 12469.
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Hocine Nebair, Bachir Helifa, Samir Bensaid, Sami Zidelmel & Ibn Khaldoun Lefkaier. (2022) Martensite morphology and volume fraction evaluation of dual-phase X70 steel using magnetic Barkhausen noise technique. Journal of Magnetism and Magnetic Materials 555, pages 169397.
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