In this study, we focus on analyzing the acoustic emission waveforms of the fatigue crack growth despite the conventional statistics-based analysis of acoustic emission. The acoustic emission monitoring technique is a well-known approach in the non-destructive evaluation/structural health monitoring research field. The growth of the fatigue crack causes the acoustic emission in the material that propagates in the structure. The acoustic emission happens not only from the crack growth but also from the interaction of the crack tips during the fatigue loading in the structure. The acoustic emission waveforms are generated from the acoustic emission events; they propagate and create local vibration modes along the crack faces (crack resonance). In-situ fatigue and acoustic emission experiments were conducted to monitor the acoustic emission waveforms from the fatigue cracks. Several test specimens were used in the fatigue experiments, and corresponding acoustic emission waveforms were captured. The acoustic emission waveforms were analyzed and distinguished into three types based on the similar nature in both time and frequency domains. Three-dimensional harmonic finite element analyses were performed to identify the local vibration modes. The local crack resonance phenomenon has been observed from the finite element simulation that could potentially give the geometric information of the crack. The laser Doppler vibrometry experiment was performed to identify the crack resonance phenomenon, and the experimental results were used to verify the simulated results.

The acoustic emission (AE) waveforms from a fatigue crack advancing in a thin metallic plate possess diverse and complex spectral signatures. In this article, we analyze these waveform signatures in coordination with the load level during cyclic fatigue. The advancing fatigue crack may generate numerous AE hits while it grows under fatigue loading. We found that these AE hits can be sorted into various groups based on their AE waveform signatures. Each waveform group has a particular time-domain signal pattern and a specific frequency spectrum. This indicates that each group represents a certain AE event related to the fatigue crack growth behavior. In situ AE-fatigue experiments were conducted to monitor the fatigue crack growth with simultaneous measurement of AE signals, fatigue loading, and optical crack growth measurement. An in situ microscope was installed in the load-frame of the mechanical testing system (MTS) to optically monitor the fatigue crack growth and relate the AE signals with the crack growth measurement. We found the AE signal groups at higher load levels (75%-85% of maximum load) were different from the AE signal groups that happened at lower load levels (below 60% of load level). These AE waveform groups are highly related to the fatigue crackrelated AE events. These AE signals mostly contain the higher frequency peaks (100 kHz, 230 kHz, 450 kHz, 550 kHz). Some AE signal groups happened as a clustered form that relates a sequence of small AE events within the fatigue crack. They happened at relatively lower load level (50%-60% of the maximum load). These AE signal groups may be related to crack friction and micro-fracture during the friction process. These AE signals mostly contain the lower frequency peaks (60 kHz, 100 kHz, 200 kHz). The AE waveform based analysis may give us comprehensive information of the metal fatigue.

In this article, estimation of crack size, shape, and orientation was investigated numerically and experimentally using Lamb waves. A hybrid global–local approach was used in conjunction with the imaging methods for the numerical simulation. The hybrid global–local approach allowed fast and efficient prediction of scattering wave signals for Lamb wave interaction with crack from various incident directions. The simulation results showed the directionality effect of the scattering wave signals and suggested an optimum transmitter–sensor configuration. Two imaging methods were used: one involves the synthetic time reversal concept and the other involves Gaussian distribution function. Both imaging methods show very good agreement during simulations. Experiments were designed and conducted based on the simulated results. A network of eight piezoelectric wafer active sensors was used to capture the scattering waves from the crack. Both the pitch-catch and pulse-echo experimental modes were used. The directionality effect of incident Lamb waves on the imaging results was studied. The effect of summation, multiplication, and combined algorithms for each imaging method was studied. It was found that both methods can successfully predict the crack size and orientation. An attempt was made to use these imaging methods for detecting and sizing smaller sized damage (1- to 3-mm-diameter hole). It was found that these methods can successfully localize the hole, but size estimation was a bit challenging because of the smaller dimensions. The scattering waves for various hole sizes were studied.

In this article, the effect of the acoustic emission sensor on the acoustic emission waveforms from fatigue crack growth in a thin aerospace specimen is presented. In situ acoustic emission fatigue experiments were performed on the test coupons made of aircraft grade aluminum plate. Commercial Mistras S9225 acoustic emission sensor and piezoelectric wafer active sensor were used to capture the acoustic emission waveforms from the fatigue crack. It has been shown that the piezoelectric wafer active sensor transducer successfully captured the fatigue crack–related acoustic emission waveforms in the thin plate. The piezoelectric wafer active sensor transducer seems to capture more frequency information of the acoustic emission waveform than the conventional acoustic emission sensor in this particular application. We have also shown the evolution of the acoustic emission waveforms as the fatigue crack grows. The signatures of the fatigue crack growth were captured by the evolution of the acoustic emission waveforms. This waveform evolution is highly related to the physical boundary conditions of the cracks as well as the fatigue crack growth mechanism. The fatigue loading and acoustic emission measurement were synchronized using the same acoustic emission instrumentation. This synchronization provided the exact load level when the acoustic emission signals had occurred during the fatigue crack growth.

In this article, ultrasonic guided wave propagation and interaction with the rivet hole cracks has been formulated using closed-form analytical solution while the local damage interaction, scattering, and mode conversion have been obtained from finite element analysis. The rivet hole cracks (damage) in the plate structure gives rise to the non-axisymmetric scattering of Lamb wave, as well as shear horizontal (SH) wave, although the incident Lamb wave source (primary source) is axisymmetric. The damage in the plate acts as a non-axisymmetric secondary source of Lamb wave and SH wave. The scattering of Lamb and SH waves are captured using wave damage interaction coefficient (WDIC). The scatter cubes of complex-valued WDIC are formed that can describe the 3D interaction (frequency, incident direction, and azimuth direction) of Lamb waves with the damage. The scatter cubes are fed into the exact analytical framework to produce the time domain signal. This analysis enables us to obtain the optimum design parameters for better detection of the cracks in a multiple-rivet-hole problem. The optimum parameters provide the guideline of the design of the sensor installation to obtain the most noticeable signals that represent the presence of cracks in the rivet hole.