Wavelets and wavelet transforms have become popular new tools in the fields of signal processing and mathematical modeling because of the various advantages they have over traditional techniques. The Fourier Transform decomposes a signal into a frequency spectrum at the loss of time domain information. Wavelet transforms involve decomposing a signal into various levels to study frequency patterns over time. High frequency characteristics in the lower levels and low frequency characteristics in the higher levels allow the analyst to make predictions regarding the nature of the signal.
This case involved the study of tuning fork frequency characteristics using the Discrete Wavelet Transform. Experimental data for two tuning forks of different frequencies was taken and analyzed in order to study the frequency quality, noise present, and abnormalities in the signal. Conclusions and explanations of the abnormalities contained in the signals were determined by creating models using wavelet algorithms contained in the Matlab Wavelet Toolbox.
Library of Congress Subject Headings
Signal processing--Mathematics; Wavelets (Mathematics); Harmonic analysis
Mechanical Engineering (MS)
Department, Program, or Center
Mechanical Engineering (KGCOE)
Josef S. Török
Richard G. Budynas
Mark H. Kempski
Smertneck, John E., "Wavelet analysis of acoustic signals" (2000). Thesis. Rochester Institute of Technology. Accessed from
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