• Login
    View Item 
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    The effectiveness of various chatter detection methods under noisy conditions

    Thumbnail
    View/Open
    LU-THESIS-2020.pdf (1.197Mb)
    Date
    2020-05-17
    Author
    Lu, Lance C.
    Metadata
    Show full item record
    Abstract
    Unmanned operations are sought after in manufacturing processes such as milling and lathing. During these processes, the detection and mitigation of machine tool chatter is critical. The veracity of these methods under noise conditions that would be found in a live factory environment is not well understood. This study aims to evaluate the performance of various classification methods for the detection of chatter under periodic and white noise. Different training methods and artificial noise injection are used to highlight the benefits and pitfalls of the different methods for chatter detection. It is found that machine learning models like Support Vector Machines have a significant ability to classify noisy data even when untrained on noise.
    URI
    http://hdl.handle.net/1853/63598
    Collections
    • Georgia Tech Theses and Dissertations [23877]
    • School of Mechanical Engineering Theses and Dissertations [4086]

    Browse

    All of SMARTechCommunities & CollectionsDatesAuthorsTitlesSubjectsTypesThis CollectionDatesAuthorsTitlesSubjectsTypes

    My SMARTech

    Login

    Statistics

    View Usage StatisticsView Google Analytics Statistics
    facebook instagram twitter youtube
    • My Account
    • Contact us
    • Directory
    • Campus Map
    • Support/Give
    • Library Accessibility
      • About SMARTech
      • SMARTech Terms of Use
    Georgia Tech Library266 4th Street NW, Atlanta, GA 30332
    404.894.4500
    • Emergency Information
    • Legal and Privacy Information
    • Human Trafficking Notice
    • Accessibility
    • Accountability
    • Accreditation
    • Employment
    © 2020 Georgia Institute of Technology