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Adaptive Methods within a Sequential Bayesian Approach for Structural Health Monitoring

Abstract Structural integrity is an important characteristic of performance for critical components used in applications such as aeronautics, materials, construction and transportation. When appraising the structural integrity of these components, evaluation methods must be accurate. In addition to possessing capability to perform damage detection, the ability to monitor the level of damage over time can provide extremely useful information in assessing the operational worthiness of a structure and in determining whether the structure should be repaired or removed from service. In this work, a sequential Bayesian approach with active sensing is employed for monitoring crack growth within fatigue-loaded materials. The monitoring approach is based on ... (more)
Created Date 2013
Contributor Huff, Daniel William (Author) / Papandreou-Suppappola, Antonia (Advisor) / Kovvali, Narayan (Committee member) / Chakrabarti, Chaitali (Committee member) / Chattopadhyay, Aditi (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / Aerospace engineering / Mechanical engineering / adaptive sensing / hidden Markov models / Structural Health Monitoring / time-frequency
Type Doctoral Dissertation
Extent 144 pages
Language English
Reuse Permissions All Rights Reserved
Note Ph.D. Electrical Engineering 2013
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis