Application of entropy in identification of breathing cracks in a beam structure: Simulations and experimental studies

Abstract

A cantilever beam with a breathing crack is studied to detect the crack and evaluate the crack depth using entropy measures. During the vibration in engineering structures, fatigue cracks undergo the status from close-to-open (and open-to-close) repetitively leading to a crack breathing phenomenon. Entropy is a measure, which can quantify the complexity or irregularity in system dynamics, and hence employed to quantify the bi-linearity/irregularity of the vibration response, which is induced by the breathing phenomenon of a crack. A mathematical model of harmonically excited unit length steel cantilever beam with a breathing crack located near the fixed end is established, and an iterative numerical method is applied to generate accurate time domain vibration responses. The steady-state time domain vibration signals are pre-processed with wavelet transformation, and the bi-linearity/irregularity of the vibration signals due to breathing effect is then successfully quantified using both sample entropy and quantized approximation of sample entropy to detect and estimate the crack depth. It is observed that the method is capable of identifying crack depths even at very early stages of 3% of the beam thickness with significant increment in the entropy values (more than 200%) compared to the healthy beam. In addition, experimental studies are conducted, and the simulation results are in good agreement with the experimental results. The proposed technique can also be applied to damage identification in other types of structures, such as plates and shells.

Performance of Damage Identification Based on Directional Wavelet Transforms and Entopic Weights Using Experimental Shearographic Testing Results

“…A similar approach using WPT was presented in [ 52 , 53 ]. The improvement of this approach was proposed in [ 54 ], where the authors defined two entropy measures using probability analysis for the identification and quantification of cracks in beams. Another approach was proposed in [ 55 , 56 ], where the authors determined entropy of the frequency response spectra of the tested beam- and plate-like structures.…”

Breathing crack damage diagnostic strategy using improved MFCC features

“…Only fewer techniques (Asnaashari and Sinha, 2014; Wimarshana et al, 2017, 2018) use ambient vibration data for breathing crack identification. The reason behind this is that the presence of noise may sometimes be wrongly construed as nonlinearity and vice versa.…”

“…However, the method is highly dependent on input excitation position, crack position, crack depth and number of modes being considered. Wimarshana et al (2017, 2018) developed wavelet entropy-based approach for breathing crack identification using random vibration data. However, the work is limited to confirming the presence of a breathing crack in the structure only.…”

Novel Damage Detection Tool Based on Load Path Analysis Using Ustar (U*)

“…Frequency-shift was significantly magnified while the piezo-patch at the location of the damage was activated, giving it the potential of locating the damage. In addition to the applications of smart materials, some other algorithms and approaches (e.g., transfer matrix method [8], [9], wavelet transform [10], [11], and entropy [12]- [14]) were also introduced to help extract the damage features from the dynamic signals.…”