Crack-Length Estimation for Structural Health Monitoring Using the High-Frequency Resonances Excited by the Energy Release during Fatigue-Crack Growth

Abstract

Acoustic waves are widely used in structural health monitoring (SHM) for detecting fatigue cracking. The strain energy released when a fatigue crack advances has the effect of exciting acoustic waves, which travel through the structures and are picked up by the sensors. Piezoelectric wafer active sensors (PWAS) can effectively sense acoustic waves due to fatigue-crack growth. Conventional acoustic-wave passive SHM, which relies on counting the number of acoustic events, cannot precisely estimate the crack length. In the present research, a novel method for estimating the crack length was proposed based on the high-frequency resonances excited in the crack by the energy released when a crack advances. In this method, a PWAS sensor was used to sense the acoustic wave signal and predict the length of the crack that generated the acoustic event. First, FEM analysis was undertaken of acoustic waves generated due to a fatigue-crack growth event on an aluminum-2024 plate. The FEM analysis was used to predict the wave propagation pattern and the acoustic signal received by the PWAS mounted at a distance of 25 mm from the crack. The analysis was carried out for crack lengths of 4 and 8 mm. The presence of the crack produced scattering of the waves generated at the crack tip; this phenomenon was observable in the wave propagation pattern and in the acoustic signals recorded at the PWAS. A study of the signal frequency spectrum revealed peaks and valleys in the spectrum that changed in frequency and amplitude as the crack length was changed from 4 to 8 mm. The number of peaks and valleys was observed to increase as the crack length increased. We suggest this peak–valley pattern in the signal frequency spectrum can be used to determine the crack length from the acoustic signal alone. An experimental investigation was performed to record the acoustic signals in crack lengths of 4 and 8 mm, and the results were found to match well with the FEM predictions.

Experimental Investigation on Roughness Parameters of 42CrMo4 Steel Surface During Nitrocarburizing Treatment

“…There is a relationship between high peaks and the two phenomena of friction and wear, according to studies [24,25]. Additionally, deeper grooves and valleys in the surface texture might cause crack propagation [26,27] and corrosion [28,29]. It can be seen from the table 1 and the Fig.…”

Piezoelectric Wafer Active Sensor Transducers for Acoustic Emission Applications

“…In order to check our instrumentation in this round robin fashion, two actuation functions were used for the transmitting PWAS. One function was a smooth-step function associated with fatigue crack growth acoustic emissions in the finite element modeling of fatigue cracks, while the other function was a smooth-delta function associated with fatigue crack rubbing and clapping [ 16 , 17 , 18 ]. Each function had a rise time of 0.5 microseconds, with each function’s equations, waveforms and frequency spectrums being shown in Figure 3 .…”

An Artificial Intelligence Approach to Fatigue Crack Length Estimation from Acoustic Emission Waves in Thin Metallic Plates

“…As previously described in Section 3 and Ref. [22], the fundamental concept is that these AE signals will differ in various characteristics, specifically in the frequency domain. The goal is to build an artificial intelligence system capable of discerning these distinctions and accurately predicting the crack length from the AE signal.…”

“…While many researchers have used sensors to capture AE waves and have analyzed the wave characteristics, not much research has been performed to establish a relationship between the length of a fatigue crack and the AE waveform signatures. Some initial novel work from Joseph et al [22] presents analytical and experimental evidence that such a relationship may exist within fatigue crack AE signals. The general concept is that when energy is released from the fatigue crack, it resonates with the crack forming a standing wave pattern.…”