Acoustic emission (AE) is a well-developed structural health monitoring method that relies on capturing the elastic waves generated by the energy released during crack formation in a solid medium A novel modeling approach based on moment tensor concept is presented in this paper to simulate AE due to fatigue crack. The AE source due to fatigue crack growth and rubbing/clapping was assumed as components of moment tensor source, and the simulation was performed. The simulation results were compared with experimental observations, and a good agreement of simulation and experiment was observed.
Barely visible impact damage (BVID) due to low velocity impact events in composite aircraft structures are becoming extremely prevalent. BVID can have an adverse effect on the strength and safety of the structure. During aircraft inspections it can be extremely difficult to visually detect BVID. Moreover, it is also a challenge to ascertain if the BVID has in-fact caused internal damage to the structure or not. In this paper, multiple 2-mm quasi-isotropic carbon fiber reinforced polymer (CFRP) composite coupons were impacted using the ASTM D7136 standard in a drop weight impact testing machine to determine the mass, height and energy parameters to obtain approximately 1" impact damage size in the coupons iteratively. For subsequent impact tests, four piezoelectric wafer active sensors (PWAS) were bonded at specific locations on each coupon to record the acoustic emission (AE) signals during the impact event using the MISTRAS micro-II digital AE system. Impact tests were conducted on these instrumented 2-mm coupons using previously calculated energies that would create either no damage or 1" impact damage in the coupons. The obtained AE waveforms and their frequency spectrums were analyzed to distinguish between different AE signatures. From the analysis of the recorded AE signals, it was determined if the structure had indeed been damaged due to the impact event or not. Using our proposed structural health monitoring technique, it could be possible to rapidly identify impact events that cause damage to the structure in real-time and distinguish them from impact events that do not cause damage to the structure. An invention disclosure describing our acoustic emission structural health monitoring technique has been filed and is in the process of becoming a provisional patent.
A novel method is proposed in this paper to extract acoustic emission (AE) source using Helmholtz potentials approach. In order to characterize the source in terms of potentials the underlying physics is to detect the AE signals and then develop an inverse algorithm to characterize the source. According to the new concept, the source can be characterized it provides the excitation potential information from the crack and that can be used to diagnose the crack (crack type and crack growth etc.). An AE experiment was designed to measure the acoustic emissions from the fatigue crack growth. A test specimen was made of 1 mm thick 304-steel material. A small hole (1 mm diameter) was drilled at the center of the specimen to initiate the fatigue crack. The specimen was subjected to the cyclic loadings by using the hydraulic MTS machine. AE waveforms are generated by convolutions of AE source functions, plate transfer functions. An inverse algorithm was developed to characterize the source of AE signal. AE signal analysis are done to determine AE source function using deconvolution process.
Crack rubbing or clapping in metallic structures generates acoustic emission (AE) signals. Such AE signals need to be distinguished from AE signal due to fatigue crack growth event. AE signal due to crack rubbing or clapping of fatigue generated crack was studied for a plate specimen. 20 mm fatigue crack was generated in a 1 mm thick aluminum plate specimen. Vibration-induced excitation was performed on the specimen to induce crack faying surface-motion for AE signal generation. Various specimen resonances have different crack faying surface motions, which were studied from FEM analysis. Modeshapes and crack faying surface motions of the specimen are studied at 35 Hz and 180 Hz specimen resonances. AE signals at various specimen resonances were recorded by piezoelectric wafer active sensors (PWAS) and the recorded waveforms are analyzed to obtain AE signatures. At various specimen resonances, AE signals have different signatures due to the change in crack faying surface motions. AE recording was done by using multiple PWAS sensors placed at various distances from the crack. The difference in AE signals close to crack and distant from crack as well as the geometric spreading of AE signals originating due to crack rubbing was studied from multi-sensor experiments.
TN32 casks are multi-layer cylindrical structures used for storage of nuclear spent fuel. The National Center for Physical Acoustics at the University of Mississippi has manufactured a scaled down model of the TN32 cask. To identify the most relevant nondestructive evaluation parameters, which will be useful while doing experiments on real TN32 casks, a series of experiments have been conducted on TN32 cask model. This paper discusses the data analysis of the experiments conducted on the cask model and the conclusions based on those experiments. Elastodynamic waves are generated in the cask model by pencil lead break and hammer hit excitation and the waves in the cask at certain locations are sensed using piezoelectric wafer active sensors (PWAS). The waveforms and frequency spectrums of waveforms arriving at PWAS are studied. There are two types of joints on the cask model: structures joined using adhesives and structures joined using press fit. The effects of various joints in the structure on elastodynamic wave propagation are also studied. Pitch catch experiments on the cask was also done using in plane excitation using PWAS. The most sensitive frequency for the cask model was identified from the frequency response spectrum obtained from a wide band chirp excitation. The influence of various joints on the frequency response spectrum is also studied. Analytical modeling of cask geometry for a given excitation is done using Normal Mode Expansion (NME) technique. Prediction of wave propagation through the scaled down model is done based on the theoretical expression derived.
Acoustic emission is a widely used and efficient method for structural damage monitoring. Analytical modeling of wave propagation due to dislocations by considering the source as a self-equilibrating moment tensor is a commonly used approach is seismology. In this paper the acoustic emission source definition using moment tensor approach is studied and tried to implement it in thin plates with micro crack acoustic emission source. Depending upon the characteristic of micro crack formed the moment tensor excitation also changes. A study has done to identify the moment tensor components for mod 1, mode 2 or mode 3 like fracture micro crack formation from the classical definition of moment tensor.
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