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Vibration-Based Techniques for Damage Detection and Health Monitoring of Mechanical Systems



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Vibration Based Techniques for Damage Detection and Health Monitoring of Mechanical Systems by Adrian I Cuc Bachelor of Science Politehnica University of Timisoara 1996 Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in the Department of Mechanical Engineering College of Engineering Information Technology University of South Carolina 2002 Department of Mechanical Engineering Director of Thesis Department of Mechanical Engineering Second Reader Dean of the Graduate School ACKNOWLEDGMENTS Building a strong education is a hard long and beautiful journey University of South Carolina added an important and substantial chapter to my professional education I would like to thank my academic advisor Dr Victor Giurgiutiu for his understanding support and guidance throughout the years I have spent at USC I would also like to thank to all the professors who have shared with me their knowledge throughout my education Special thanks go to Dr Leonid Gelman for his help and support In addition I would like to sincerely thank my colleagues and friends Jing Jing Jack Bao Max Fitzgerald Paulette Goodman Florin Jichi Greg Nall Mattias Ohlsson Radu Pomirleanu Andrew Rekers and Andrei Zagrai for their support and for having such a great time My thanks go also to the South Carolina Army National Guard Mr Lem Grant and Tim Cook for knowledge they shared with me The financial support of the South Carolina Army National Guard is gratefully acknowledged Last but not least I would like to express my deeply gratitude to my parents without whom none of this would have been possible ii ABSTRACT The state of the art in vibration based damage detection and health and usage monitoring is reviewed The damage detection concepts and the signal analysis techniques are examined explained and compared Latest advances in signal processing methodologies that are of relevance to vibration based damage detection e g Wavelet Transform and Wigner Ville distribution are



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