A MOBILE REAL-TIME SYSTEM FOR STRESS STATE DIAGNOSTICS AND RESIDUAL LIFE PREDICTION OF STRUCTURAL COMPONENTS

Mykola Gerasymenko

doi:10.36074/logos-06.02.2026.027

A MOBILE REAL-TIME SYSTEM FOR STRESS STATE DIAGNOSTICS AND RESIDUAL LIFE PREDICTION OF STRUCTURAL COMPONENTS

Mykola Gerasymenko

Conference proceedings: Sammlung wissenschaftlicher Arbeiten «ΛΌГOΣ» zu den Materialien der IX internationalen wissenschaftlich-praktischen Konferenz «Grundlagen der modernen wissenschaftlichen Forschung» (Zürich, Schweizerische Eidgenossenschaft; 6. Februar, 2026)

Section: Automation and Appliances making

Publication date: 2026/02/06

Pages: 156-158

DOI: 10.36074/logos-06.02.2026.027

ISBN: 978-617-8440-87-9

Publisher: BOLESWA Publishers

Language: en

PDF for indexing Original PDF in OJS archive DOI

Abstract

This paper presents a mobile real-time system for diagnostics of the stress state and prediction of the residual life of structural components operating under intensive dynamic loading conditions. The proposed approach is based on the use of operational data throughout the product life cycle and aligns with the Industry 4.0 paradigm, where information obtained during the operational phase is used to support technical inheritance and the structural evolution of engineering products.

Author affiliations

Mykola Gerasymenko: «Kharkiv National University of Radio Electronics», UKRAINE; ORCID

References

Lachmayer, R., Mozgova, I., Gottwald, P. Formulation of Paradigm of Technical Inheritance, Proceedings of the 20th International Conference on Engineering Design (ICED15), Vol. 8, Milan, Italy, 27.-30.07.2015, (2015), p. 271-278.
Demminger, C., Mozgova, I., Quirico, M., Uhlich, F., Denkena, B., Lachmayer, R., Nyhuis P. The Concept of Technical Inheritance in Operation: Analysis of the Information Flow in the Life Cycle of Smart Products, Proceedings of 3rd International Conference on Systemintegrated Intelligence (SysInt 2016), Procedia Technology, Vol. 26, (2016), p. 79-88, ISSN 2212-0173. http://dx.doi.org/10.1016/j.protcy.2016.08.012
Mozgova, I., Yanchevskyi, I., Gerasymenko, M., & Lachmayer, R. (2018). Mobile automated diagnostics of stress state and residual life prediction for a component under intensive random dynamic loads. Procedia Manufacturing, 24, 210–215. 4th International Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production. https://doi.org/10.1016/j.promfg.2018.06.037
Schijve J. Fatigue of structures and materials in the 20th century and the state of the art. Materials Science, 39(8), (2003), p. 679-702. http://dx.doi.org/10.1016/s0142-1123(03)00051-3
Goto, S., Tsukamoto, K. On-line residual life prediction including outlier elimination for condition based maintenance. J. of Innovative Computing, Information and Control. Vol. 8, N. 3(B), (2012), p. 2193-2202.
Lachmayer, R., Yanchevskyi, I., Mozgova, I., Gottwald, P. Identification of dynamic loads applied to an elastically deformed element of constructions, Journal of Applied and Computational Mechanics, Applied and Computational Mechanics, vol. 12, Iss. 1, pp. 17–32, 2018. http://dx.doi.org/10.24132/acm.2018.365
Mozgova. I. Intelligente Datenanalyse für die Entwicklung neuer Produktgenerationen. Proceedings of the Wissenschaftsforum Intelligente Technische Systeme (WInTeSys), 11. und 12.05.2017, Paderborn, Germany. Heinz Nixdorf Institut, Vol. 369, (2017), p. 335-346.

[1] Lachmayer, R., Mozgova, I., Gottwald, P. Formulation of Paradigm of Technical Inheritance, Proceedings of the 20th International Conference on Engineering Design (ICED15), Vol. 8, Milan, Italy, 27.-30.07.2015, (2015), p. 271-278.

[2] Demminger, C., Mozgova, I., Quirico, M., Uhlich, F., Denkena, B., Lachmayer, R., Nyhuis P. The Concept of Technical Inheritance in Operation: Analysis of the Information Flow in the Life Cycle of Smart Products, Proceedings of 3rd International Conference on Systemintegrated Intelligence (SysInt 2016), Procedia Technology, Vol. 26, (2016), p. 79-88, ISSN 2212-0173. http://dx.doi.org/10.1016/j.protcy.2016.08.012

[3] Mozgova, I., Yanchevskyi, I., Gerasymenko, M., & Lachmayer, R. (2018). Mobile automated diagnostics of stress state and residual life prediction for a component under intensive random dynamic loads. Procedia Manufacturing, 24, 210–215. 4th International Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production. https://doi.org/10.1016/j.promfg.2018.06.037

[4] Schijve J. Fatigue of structures and materials in the 20th century and the state of the art. Materials Science, 39(8), (2003), p. 679-702. http://dx.doi.org/10.1016/s0142-1123(03)00051-3

[5] Goto, S., Tsukamoto, K. On-line residual life prediction including outlier elimination for condition based maintenance. J. of Innovative Computing, Information and Control. Vol. 8, N. 3(B), (2012), p. 2193-2202.

[6] Lachmayer, R., Yanchevskyi, I., Mozgova, I., Gottwald, P. Identification of dynamic loads applied to an elastically deformed element of constructions, Journal of Applied and Computational Mechanics, Applied and Computational Mechanics, vol. 12, Iss. 1, pp. 17–32, 2018. http://dx.doi.org/10.24132/acm.2018.365

[7] Mozgova. I. Intelligente Datenanalyse für die Entwicklung neuer Produktgenerationen. Proceedings of the Wissenschaftsforum Intelligente Technische Systeme (WInTeSys), 11. und 12.05.2017, Paderborn, Germany. Heinz Nixdorf Institut, Vol. 369, (2017), p. 335-346.