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Description:
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In 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 . |