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Health Management and Prognostics of Complex Structures and Systems

Abstract This dissertation presents the development of structural health monitoring and prognostic health management methodologies for complex structures and systems in the field of mechanical engineering. To overcome various challenges historically associated with complex structures and systems such as complicated sensing mechanisms, noisy information, and large-size datasets, a hybrid monitoring framework comprising of solid mechanics concepts and data mining technologies is developed. In such a framework, the solid mechanics simulations provide additional intuitions to data mining techniques reducing the dependence of accuracy on the training set, while the data mining approaches fuse and interpret information from the targeted system enabling th... (more)
Created Date 2019
Contributor Li, Guoyi (Author) / Chattopadhyay, Aditi (Advisor) / Mignolet, Marc (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Yekani Fard, Masoud (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Subject Mechanical engineering / Carbon Fiber Composite / Machine Learning / Prognostics / Structural Health Monitoring / System Health Management / Ultrasonic Guided Wave
Type Doctoral Dissertation
Extent 213 pages
Language English
Note Doctoral Dissertation Mechanical Engineering 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis