Real‐time reference‐free breathing crack identification using ambient vibration data

Abstract

Summary A novel dynamic principal component analysis (DPCA)‐based baseline‐free damage diagnostic technique addressing breathing crack detection, localization, and characterization is proposed using ambient vibration data in the time domain. The nonlinear components sensitive to breathing crack, buried in the noisy responses, are first reconstructed by the elimination of the active principal components contributing to the total response using DPCA. A temporal damage sensitive feature based on the evolution of the variation of the residual principal component over time is proposed for confirming the presence and identifying the exact time instant of breathing crack in the structure. Besides detection, three new damage localization indices based on the fractal dimensional analysis of the residual response, first residual principal component vector, and directional angle are proposed for breathing crack localization. The effectiveness of the proposed DPCA 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 DPCA approach.

A novel time domain-based multiple breathing crack diagnosis technique using Quadratic-Teager Kaiser Energy (Q-TKE)

“…The advantages of bitone over single tone in nonlinear feature extraction have been demonstrated very clearly in the literature. 5–7…”

“…The advantages of bitone over single tone in nonlinear feature extraction have been demonstrated very clearly in the literature. [5][6][7] (a) (b) Breathing crack localization-robustness and sensitivity to different parameters. Investigations have been carried out to evaluate the sensitivity of the proposed multiple breathing crack localization algorithm to the measurement noise and also the excitation location on the beam, and several numerical experiments have been conducted.…”

“…Identification of fatigue-breathing cracks at an early stage offers critical information about the health of the structures, aiding in preventing catastrophic failure and saving human lives. Several vibration-based methods have been proposed by researchers [1][2][3][4][5][6][7] for breathing crack identification (addressing all three steps: detection, localization, and characterization) using single tone, bitone, and multi-tone harmonic vibration data. Due to the periodic opening and closing of fatigue cracks under single-tone harmonic excitation, the structure vibrates at the excitation frequency and higherorder harmonics.…”

“…While the dynamic behavior of beams with a single breathing crack has received much attention, [3][4][5][6][7][8][9][10][11][12] very limited investigations have been reported on multiple breathing cracks. [13][14][15][16][17][18][19] As the number of breathing cracks present in the beams and their spatial locations is usually not known a priori, detection and localization of multiple breathing cracks are much more challenging.…”

“…There exists a lot of research evidence on extraction of low amplitude nonlinear features such as superharmonics and mixed harmonics or intermodulations from the vibration response using frequency domain approaches. [1][2][3][4][5][6][7][8] Only very few studies are completely time-domain approaches [22][23][24][25] and they mostly aim at addressing single breathing crack identification. The extraction and enhancement of the nonlinear features in the time domain especially toward multiple breathing crack localization is highly complex and challenging.…”