Browsing by Subject "Acoustic emission testing"
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Item Acoustic emission signature analysis of failure mechanisms in fiber reinforced plastic structures(2002) Ativitavas, Nat; Fowler, Timothy John; Fowler, David W.The objective of the research program was to develop reliable pattern recognition and neural network analysis methods to determine the failure mechanism signatures in fiber reinforced plastic structures from acoustic emission (AE) data. The AE database was collected from a range of test specimens. Visual inspection and observation with a scanning electron microscope were performed to identify failure mechanisms in the specimens at various load levels. It was found that different types of specimen and structural loading yielded different types of failure. The failure mechanisms of interest were matrix cracking, debonding, delamination, and fiber breakage. Two method of analysis were used to determine the AE signatures. The first was visual AE pattern recognition. This analysis used a comparison of dissimilarities among AE correlation plots of data from different specimens. The results showed several AE signatures. The analysis also explains the correlation of material properties to failure mechanism evolution. The second analysis method was the use of neural networks to perform AE pattern recognition. The neural networks were trained using AE data in order to perform two tasks: determine the failure mechanisms and to assess the damage severity. The performance of the networks was found to be excellent for the first task and promising for the second task. The neural network was also applied to additional AE data from full-scale and coupon tests. By comparing the results from the network with visually observed damage, the network results are shown to be very reliable in determining failure mechanisms.Item Detection of transverse cracking in a hybrid composite laminate using acoustic emission(2003-12) Jong, Hwai-jiang, 1962-; Schapery, Richard Allan; Ravi-Chandar, K.Transverse cracking detection in a uniaxially-loaded symmetric cross-ply hybrid laminate containing 0◦ IM7/8552 carbon/epoxy and a very thin 90◦ S2/8552 glass/epoxy layer is studied using the acoustic emission (AE) technique. By conducting modal-based AE experiments and analysis, we investigate some parameters that can be used as the waveform signatures to identify transverse crack growth in the hybrid laminate. Wave dispersion relations of the hybrid laminate are established, and a comparison with those from a material homogenization model based on the equivalent stiffness is made. It is found that material homogenization is not accurate for predicting wave dispersion in the hybrid laminate. Wave dispersion for a homogeneous IM7/8552 unidirectional plate is also constructed. Cut-off frequencies belonging to various wave modes are discussed concerning their significance in interpreting AE signals. The wave attenuation behaviors that exist in the hybrid laminate and in the homogeneous IM7/8552 plate are compared and discussed using the finite element method (FEM). The use of singular elements dealing with the high strain gradient near the crack tip is addressed for convergence purposes. It is shown by the FEM results and demonstrated in the AE experiments that wave attenuation in the cross-ply hybrid laminate is much stronger than in the plain IM7/8552 plate. A simple calibration method for the AE sensors is discussed. Some important aspects in conducting an AE experiment, such as the sensor averaging effect and sensor frequency response range, are addressed. A new source location method based on the waveform’s first peak search and the associated primary frequency content is proposed. The accuracy of the source location method is verified by pencil-lead break experiments. The so-called symmetric energy fraction (SEF) of the AE signals in conjunction with the finite element analysis result in identification of the transverse cracking event. Lastly, a material failure kinetics-based characterization of the transverse cracking process is proposed in terms of the unloading forcing function on the transverse crack face. Finite element results based on this loading are compared to the AE signals.Item Discrete wavelet analysis of acoustic emissions during fatigue loading of carbon fiber reinforced composites(Texas Tech University, 1996-05) Kamala, Girish P.Acoustic Emissions (AE) are generated during operational loading of Fiber Reinforced Composite (FRC) materials due to various sources of fracture. These sources which include matrix fracture, fiber fracture, splitting and delamination could be generated individually or simultaneously. The multiplicity of defects and failure modes creates problems in identifying and distinguishing various sources of emissions. This analysis is further complicated due to the friction related emissions (generated during grating of newly generated damage surfaces and fretting of broken fibers with matrix) that mask the actual signal and in most cases, exceeds the emissions from actual damage. The purpose of this thesis is to investigate the appUcability of discrete wavelet transforms in the analysis and time-frequency breakdown of AE signals detected during fatigue loading of FRC materials. The first objective is to decompose the AE signals into different levels based on the central frequency around which the emissions are generated. The second objective is to identify the frequency at which friction based emissions are generated. The final objective is to determine if a possibility exists to associate various failure modes with specific frequencies.Item Wavelet-based acoustic emission analysis of composite materials(Texas Tech University, 1996-08) Qi, GangIn this dissertation, a methodology for time-frequency analysis of acoustic emission (AE) signals generated due to static loading of composite specimen is presented. The tool is based on a recently developed mathematical transform called the wavelet transform. Two aspects of AE-based nondestructive evaluation (NDE) are failure mode identification and residual strength prediction. In this work, the wavelet-based AE method is applied to these two aspects of AE-based NDE. Presently, the public literature review indicates that AE techniques are dominated by time domain analysis methods. It can be seen that these methods have matured into tools which provide satisfactory results. There are limited results available that use frequency domain techniques, however, there is valuable information available in the frequency domain. Thus, it is evident that there is a need for an AE analysis technique that simultaneously utilizes both the time and frequency domains. In this dissertation, a hybrid technique is developed. With the application of wavelet transforms to the failure mode identification, the AE signals are decomposed into different wavelet levels. A general trend is observed by investigating the energy-frequency distribution of the decomposed AE signals. This trend indicates that the energy in the AE signals is essentially concentrated in three levels (seven, eight, and nine), representing frequency rages of 50-150 kHz, 150-250 kHz, and 250-310 kHz. Furthermore, the energy percentages in levels seven, eight, and nine are determined to be 8%, 15%, and 75%, respectively. The analysis indicates that the three dominant wavelet levels may be related to different failure modes associated with the fracture of CFR composites. In the prediction of residual strength, the ability of the wavelet transform to enhance the signal to noise ratio is employed. The exponential constant in value used to determine the relationship between stress and stress intensity factor are compared relative to classical fracture mechanics and AE techniques. In the comparison study, the conventional and wavelet-based AE techniques are presented side-by-side to show the advantage of wavelet-based methods. The results verify that the wavelet-based method improves on the results relative to classical fracture mechanics methods.