Damage detection in beams from modal and wavelet analysis using a stationary roving mass and noise estimation

Abstract

This paper uses the Continuous Wavelet Transform Analysis on mode shapes for damage identification. The wavelet analysis is applied to the difference in the mode shapes between a healthy and a damaged state. The paper also includes a novel methodology for estimating the level of noise of the experimental mode shapes based on a standard Signal to Noise Ratio (SNR). The estimated SNRs are used for identifying and making emphasis on the less noisy data. Moreover, a mass attached to the structure is considered to enhance the sensitivity of the structure to damage. Modal analysis is performed for different positions of the mass along the beam. The results obtained for all the positions of the mass are combined so an averaging process is implicitly applied. The paper presents the results from an experimental test of a cantilever steel beam with different severity levels of damage at the same location. The results show that the use of the attached mass reduces the effect of noise and increases the sensitivity to damage. Little damage can be identified with the proposed methodology even using a small number of sensors and only the first five bending modes