Determining the Temperature Using Natural Frequencies and Artificial Intelligence

Authors

  • Alexandra-Teodora AMAN Doctoral School of Engineering, Faculty of Engineering, Babes-Bolyai University, Cluj-Napoca, Romania. Email: alexandra.aman@ubbcluj.ro. https://orcid.org/0009-0001-9220-9973
  • Zeno-Iosif PRAISACH Department of Engineering Science, Faculty of Engineering, Babes-Bolyai University, Reșița, Romania. Email: zeno.praisach@ubbcluj.ro. https://orcid.org/0000-0002-8613-8224
  • Gilbert-Rainer GILLICH Department of Engineering Science, Faculty of Engineering, Babes-Bolyai University, Reșița, Romania. Email: gilbert.gillich@ubbcluj.ro. https://orcid.org/0000-0003-4962-2567
  • Vasile Cătălin RUSU Doctoral School of Engineering, Faculty of Engineering, Babes-Bolyai University, Cluj-Napoca, Romania. Email: vasile.rusu@ubbcluj.ro.

DOI:

https://doi.org/10.24193/subbeng.2023.spiss.2

Keywords:

temperature, natural frequency, artificial intelligence, finite element method, thermal condition

Abstract

The current paper explores a novel approach for determining temperature variations by integrating the modal parameters and AI techniques. The research focuses on the development of a comprehensive dataset for training an AI model encompassing an analytical method that considers thermal conditions and natural frequencies. Traditional methods of temperature measurement, like infrared and platinum resistance thermometers, often face limitations in terms of accuracy, especially in complex or dynamic environments having an uncertainty of ±3.6°C [1], respectively ±0.2°C [2]. In this study, we propose a methodology that harnesses the inherent relationship between axial loads caused by temperature variations and the change in natural frequencies of a double clamped steel beam. The measured natural frequency data is collected and fed into the AI model, specifically, for a robust temperature estimation, obtaining a maximum predicted temperature deviation of 0.386°C.

References

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STUDIA UBB ENGINEERING, Volume 68 (LXVIII), Special Issue, 2023

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Published

2023-11-15

How to Cite

AMAN, A.-T. ., PRAISACH, Z.-I. ., GILLICH, G.-R. ., & RUSU, V. C. . (2023). Determining the Temperature Using Natural Frequencies and Artificial Intelligence. Studia Universitatis Babeș-Bolyai Engineering, 68(Special Issue), 18–26. https://doi.org/10.24193/subbeng.2023.spiss.2

Issue

Volume 68, Special Issue, 2023

Section

Articles

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