Comparative Evaluation of Frequency-Based Indicators for Crack Detection

Ioana Ţincu; Gilbert Rainer Gillich; Vasile Catalin Rusu

doi:10.24193/subbeng.2025.1

Authors

Ioana Ţincu Ph.D. Stud., Babeș-Bolyai University, Doctoral School of Engineering, P-ta Traian Vuia 1–4, 320085 Reșița, Romania, ioana.tincu@ubbcluj.ro
Gilbert Rainer Gillich Babeș-Bolyai University, Doctoral School of Engineering, P-ta Traian Vuia 1–4, 320085 Reșița, Romania. *Corresponding author: gilbert.gillich@ubbcluj.ro https://orcid.org/0000-0003-4962-2567
Vasile Catalin Rusu Babeș-Bolyai University, Department of Computer Science, Str. Mihail Kogălniceanu nr. 1, RO-400084 Cluj-Napoca, Romania, vasile.rusu@ubbcluj.ro

DOI:

https://doi.org/10.24193/subbeng.2025.1

Keywords:

Crack, Natural Frequency, Artificial Neural Network, Simulated Data, Sensitivity

Abstract

This paper compares three frequency-based damage indicators: the absolute frequency, the frequency difference, and the relative frequency shift (RFS). The indicators, calculated using mathematical relations developed by the authors, are used to create a database, and an artificial neural network (ANN) is trained on them. This network is used to assess cracks at various locations and with different depths. The frequencies obtained for these cracks are from ANSYS simulations. A comparison of the indicators is made to identify the most sensitive one. It was found that both the relative frequency shift and the frequency difference provide reliable and accurate crack position detection.

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