Identification of plastic deformations in carbon steel elements using the filtered Barkhausen Noise signal

• Autorzy: Dybała Jacek , Nadulicz Krzysztof
• Języki publikacji: EN

Abstrakty

EN

The paper presents new approach to processing the Barkhausen Noise signal in order to detect and identify plastic deformations in carbon steel. A new automatic method of Barkhausen effect signal filtration was investigated. Apart from a classical measurement of Barkhausen effect signal, for which the RMS value is assumed, the signal waveform factor was also used in analyzes. The developed approach to processing the Barkhausen Noise signal has made it possible to obtain more useful diagnostic data than those obtained from the raw signal.

Słowa kluczowe

EN

non-destructive evaluation; plastic deformation; Barkhausen noise; signal processing

PL

badania nieniszczące; odkształcenie plastyczne; szum Barkhausena; przetwarzanie sygnałów

• Wydawca: Poznan University of Technology. Institute of Applied Mechanics
• Czasopismo: Vibrations in Physical Systems
• Rocznik: 2020
• Tom: Vol. 31, nr 1
• Strony: art. no. 2020106
• Opis fizyczny: Bibliogr. 8 poz., il. kolor., wykr.

Twórcy

autor

Dybała Jacek

• Warsaw University of Technology, Faculty of Automotive and Construction Machinery Engineering, Institute of Vehicles, 84 Narbutta St., 02-524 Warsaw, Poland

autor

Nadulicz Krzysztof

• Military Institute of Armament Technology, 7 Wyszynski St., 05-220 Zielonka, Poland

Bibliografia

• 1. J. C. Sánchez, M. F. Campos, L. R. Padovese, Magnetic Barkhausen emission in lightly deformed AISI 1070 steel, Journal of Magnetism and Magnetic Materials, 324(1) (2012) 11 - 14, https://doi.org/10.1016/j.jmmm.2011.07.014.
• 2. D. C. Jiles, Dynamics of domain magnetization and the Barkhausen effect, Czechoslovak Journal of Physics, 50(8) (2000) 893 - 924, https://doi.org/10.1023/A:1022846128461.
• 3. S. Santa-aho, A. Laitinen, A. Sorsa, M. Vippola, Barkhausen Noise Probes and Modelling: A Review, Journal of Nondestructive Evaluation, 38(94) (2019), https://doi.org/10.1007/s10921-019-0636-z.
• 4. H. Chen, S. Xie, Z. Chen, T. Takagi, T. Uchimoto, K. Yoshihara, Quantitative nondestructive evaluation of plastic deformation in carbon steel based on electromagnetic methods, Materials Transactions, 55(12) (2014) 1806 - 1815, https://doi.org/10.2320/matertrans.M2014173.
• 5. D. Blažek, M. Neslušan, M. Mičica, J. Pištora, Extraction of Barkhausen noise from the measured raw signal in high-frequency regimes, Measurement, 94 (2016) 456 - 463, http://dx.doi.org/10.1016/j.measurement.2016.08.022.
• 6. B. Widrow, J. R. Glover, J. M. McCool, J. Kaunitz, C. S. Williams, R. H. Hearn, J. R. Zeidler, E. Dong Jr., R. C. Goodlin, Adaptive Noise Cancelling: Principles and Applications, Proceedings of the IEEE, 63(12) (1975) 1692 - 1716, http://dx.doi.org/10.1109/PROC.1975.10036.
• 7. J. Dybała, J. Komoda, Empirical signal decomposition methods as a tool of early detection of bearing fault, in: Eds. A. Timofiejczuk, F. Chaari, R. Zimroz, W. Bartelmus, M. Haddar, Advances in Condition Monitoring of Machinery in Non-Stationary Operations, Applied Condition Monitoring, 9, Springer International Publishing AG, Cham 2018, 147 - 156, https://doi.org/10.1007/978-3-319-61927-9_14.
• 8. N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N. C. Yen, C. C. Tung, H. H. Liu, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proceedings of the Royal Society of London, Series A - Mathematical, Physical and Engineering Sciences, 454(1971) (1998) 903 - 995, http://dx.doi.org/10.1098/rspa.1998.0193.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).