Advanced structural damage detection in steel beams using discrete wavelet transform and fast Fourier transform

This paper introduces a novel method for detecting damage in beams based on energy distribution analysis of the power spectrum (PSD). An experiment was carried out on a steel beam, where incremental cuts representing damage were introduced. At each stage, the beam was subjected to a load and its vibrations were measured to collect data. These vibration signals were then analyzed using the discrete wavelet transform (DWT), which isolates distinct signal segments that are more sensitive to the presence of damage. To further clarify the results, these signal segments were processed using the fast Fourier transform (FFT). The findings show that the power spectrum of the segmented signals is significantly more sensitive to damage compared to the power spectrum of the original signal. The study evaluates the sensitivity to damage using the energy distribution of the power spectrum in the frequency domain, while tracking changes in this energy as damage progresses. The proposed method not only accurately identifies the presence of damage but also monitors its progression over time. This offers a promising solution for predicting structural damage and conducting quality assessments, providing early warnings, and tracking the development of structural issues.