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Tytuł artykułu

Analysis of Anomalies in the Thermal-Mechanical Fatigue Process Using Selected IT Tools

Tytuł czasopisma

Archives of Foundry Engineering

Rocznik

Accepted articles

Autorzy

Jaśkowiec, K. ; Wilk-Kołodziejczyk, D. ; Nosarzewski, K.

Afiliacje

Jaśkowiec, K. : Łukasiewicz Research Network – Krakow Institute of Technology, Kraków, Poland ; Wilk-Kołodziejczyk, D. : AGH University of Science and Technology, Al. A. Mickiewicza 30, 30-059 Kraków, Poland ; Nosarzewski, K. : AGH University of Science and Technology, Al. A. Mickiewicza 30, 30-059 Kraków, Poland

Słowa kluczowe

Thermal-mechanical fatigue ; Vermicular cast iron ; Coffin method ; Isolation Forest ; One-Class SVM

Wydział PAN

Nauki Techniczne

Wydawca

The Katowice Branch of the Polish Academy of Sciences

Bibliografia

  • Domengès, B., Celis, M.M., Moisy, F., Lacaze, J. & Tonn, B. (2021). On the role of impurities on spheroidal graphite degeneracy in cast irons. Carbon. 172, 529-541 https://doi.org/10.1016/J.CARBON.2020.10.030.

  • Valle, N., Theuwissen, K., Sertucha, J. & Lacaze, J. (2012). Effect of various dopant elements on primary graphite growth. IOP Conference Series: Materials Science and Engineering. 27(1), 012026, 1-6. https://doi.org/10.1088/1757-899X/27/1/012026.

  • Mrvar, P., Petrič, M. & Terčelj, M. (2023). Thermal fatigue of spheroidal graphite cast iron. TMS Annual Meeting & Exhibition. 406-415. https://doi.org/10.1007/978-3-031-22524-6_37.

  • Fourlakidis, V., Hernando, J.C., Holmgren, D. & Diószegi, A. (2023). Relationship between thermal conductivity and tensile strength in cast irons. International Journal of Metalcasting. 17, 2862-2867. https://doi.org/10.1007/s40962-023-00970-6.

  • Wang, L., Liu, H., Huang, C., Yuan, Y., Yao, P., Huang, J. & Han, Q. (2023). A methodology to predict thermal crack initiation region of tool for high-speed milling compacted graphite iron based on three-dimensional transient thermal stress field model. The International Journal of Advanced Manufacturing Technology. 125, 2065-2075. https://doi.org/10.1007/s00170-023-10832-4.

  • Coffin, L.F. & Wesley, R.P. (1954). Apparatus for study of effects of cyclic thermal stresses on ductile metals. Journal of Fluids Engineering. 76, 923-930. https://doi.org/10.1115/1.4015019.

  • Seifert, T. & Riedel, H. (2010). Mechanism-based thermomechanical fatigue life prediction of cast iron. Part I: Models. International Journal of Fatigue. 32, 1358-1367. https://doi.org/10.1016/J.IJFATIGUE.2010.02.004.

  • Amaro, R.L., Antolovich, S.D., Neu, R.W., Fernandez-Zelaia, P. & Hardin, W. (2012). Thermomechanical fatigue and bithermal–thermomechanical fatigue of a nickel-base single crystal superalloy. International Journal of Fatigue. 42, 165-171. https://doi.org/10.1016/J.IJFATIGUE.2011.08.017.

  • Boto, F., Murua, M., Gutierrez, T., Casado, S., Carrillo, A., & Arteaga, A. (2022). Data driven performance prediction in steel making. Metals. 12(2), 172, 1-19. https://doi.org/10.3390/met12020172.

  • Li, W., Chen, H., Guo, J., Zhang, Z., Wang, Y. (2022). Brain-inspired multilayer perceptron with spiking neurons. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 18-24 June 2022 (pp. 773-783). https://doi.org/10.1109/CVPR52688.2022.00086. New Orleans, LA, USA: IEEE.

  • Shu, X., Zhang, S., Li, Y. & Chen, M. (2022). An anomaly detection method based on random convolutional kernel and isolation forest for equipment state monitoring. Eksploatacja i Niezawodność – Maintenance and Reliability. 24(4), 758-770. https://doi.org/10.17531/EIN.2022.4.16.

  • Wu, X., Kang, H., Yuan, S., Jiang, W., Gao, Q. & Mi, J. (2023). Anomaly detection of liquid level in mold during continuous casting by using forecasting and error generation. Applied Sciences. 13(13), 7457, 1-16. https://doi.org/10.3390/app13137457.

  • Liu, F.T., Ting, K.M., Zhou, Z.H. (2008). Isolation forest. In Proceedings - IEEE International Conference on Data Mining, ICDM, 15-19 December 2008 (pp. 413-422). https://doi.org/10.1109/ICDM.2008.17.

  • Seliya, N., Abdollah Zadeh, A., Khoshgoftaar, T.M. (2021). A literature review on one-class classification and its potential applications in big data. Journal of Big Data. 8, 1-31 https://doi.org/10.1186/s40537-021-00514-x.

Data

27.10.2025

Typ

Article

Identyfikator

DOI: 10.24425/afe.2025.155373 ; eISSN 2299-2944
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