LAUSR

In this paper, a new two-stage damage diagnostic technique for breathing crack identification in using improved Mel frequency Cepstral Analysis is proposed for engineering structures. The improvements such as the centre frequencies of Mel-filter bank around the resonant frequencies and the automatic selection of cut-off frequency for frequency conversion (i.e. from Mel-scale to frequency-scale) based on the energy of the response is employed in the present work to customise the estimation of Mel-frequency Cepstral Coefficients (popularly being used for speech signals) for structural vibration responses. In the first stage of the proposed improved Mel-frequency Cepstral Coefficients (MFCC) approach for breathing crack identification, the measured acceleration time history responses are converted into Mel-frequency Cepstral Coefficients using improved Mel frequency Cepstral Analysis. The Mahanabolis distance-based measure between the improved Mel-frequency Cepstral coefficients of the healthy structure and the structure with localized damage is used for confirming the presence of breathing crack using ambient vibration data during online monitoring. In the second stage, the spatial location of breathing crack is established through offline monitoring, by exciting the structure with bitone harmonic excitation. The improved Mel-filter bank energy measured spatially across the structure is used to identify the spatial location(s) of breathing crack. The effectiveness of the proposed approach is verified using the synthetic datasets of the benchmark simply supported beam with a breathing crack, provided by Helsinki Metropolia University of Applied Sciences and a numerically simulated cantilever beam with varied spatial locations and different depths of breathing crack. Finally, experimental investigations have been carried out to demonstrate the practical viability of the proposed MFCC approach. Numerical and experimental studies concluded that the proposed damage diagnostic approach is capable of detecting and localising multiple and also subtle cracks even under varying environmental conditions with noise-contaminated measurements.