• Login
    View Item 
    •   Shocker Open Access Repository Home
    • Graduate Student Research
    • GRASP: Graduate Research and Scholarly Projects
    • Proceedings 2009: 5th Annual Symposium: Graduate Research and Scholarly Projects
    • View Item
    •   Shocker Open Access Repository Home
    • Graduate Student Research
    • GRASP: Graduate Research and Scholarly Projects
    • Proceedings 2009: 5th Annual Symposium: Graduate Research and Scholarly Projects
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Damage detection in metal structures using acoustic emission

    View/Open
    GRASP5_60.pdf (137.9Kb)
    Date
    2009-05-01
    Author
    Zachary Kral
    Horn, Walter J.
    Steck, James E.
    Metadata
    Show full item record
    Citation
    Kral, Zachary, Horn, Walter and James Steck (2009). Damage Detection in Metal Structures Using Acoustic Emission . In Proceedings: 5th Annual Symposium: Graduate Research and Scholarly Projects. Wichita, KS: Wichita State University, p. 132-133
    Abstract
    The structural components of many machines remain in service far beyond their designed lifetimes. This is especially true in the field of aerospace structures, where aircraft, wind turbines, satellites, and other components are expected to be in service for decades. Therefore, a good maintenance system is desired, allowing these structures further service use, while maintaining efficiency and reliability from failures. The focus of this research paper is on developing an improved maintenance system, called structural health monitoring, using acoustic emission sensors and artificial neural networks to detect and analyze any damage well before any component failure occurs. To replicate a damaged component for this study, an experiment was performed, involving thin, flat panels of aluminum with a designed, initial crack. These panels were subjected to static loads that were increased until crack propagation occurred. Acoustic emission sensors, which detect energy released by growing cracks in the form of strain waves, were used to detect this propagation and transform the characteristics of the propagation into electrical signals. These complex signals were then analyzed through an artificial neural network system, which allowed for fast post-processing. A structural health monitoring system was found to be plausible, using real-time analysis of the aluminum panel, detecting and reporting any growing crack from a size larger than 0.05 inches, well before any failure occurred. This study proved that acoustic emission could make structural health monitoring a reality.
    Description
    Paper presented to the 5th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Hughes Metropolitan Complex, Wichita State University, May 1, 2009.

    Research completed at the Department of Aerospace Engineering, College of Engineering
    URI
    http://hdl.handle.net/10057/2273
    Collections
    • AE Graduate Student Conference Papers
    • Proceedings 2009: 5th Annual Symposium: Graduate Research and Scholarly Projects

    Browse

    All of Shocker Open Access RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsBy TypeThis CollectionBy Issue DateAuthorsTitlesSubjectsBy Type

    My Account

    LoginRegister

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    DSpace software copyright © 2002-2023  DuraSpace
    DSpace Express is a service operated by 
    Atmire NV