Date of Award
2009
Document Type
Thesis
Publication Status
Version of Record
Submission Date
October 2026
Abstract
This thesis describes a methodology for mechanical fault detection and diagnostics in an ocean turbine using vibration analysis and modeling. This methodology relies on the use of advanced methods for machine vibration analysis and health monitoring. Because of some issues encountered with traditional methods such as Fourier analysis for non stationary rotating machines, the use of more advanced methods such as Time-Frequency Analysis is required. The thesis also includes the development of two LabVIEW models. The first model combines the advanced methods for on-line condition monitoring. The second model performs the modal analysis to find the resonance frequencies of the subsystems of the turbine. The dynamic modeling of the turbine using Finite Element Analysis is used to estimate the baseline of vibration signals in sensors locations under normal operating conditions of the turbine. All this information is necessary to perform the vibration condition monitoring of the turbine.
Extent
xiv, 100 p. : ill. (some col.)
Recommended Citation
Mjit, Mustapha., "Methodology for fault detection and diagnostics in an ocean turbine using vibration analysis and modeling" (2009). Electronic Theses and Dissertations 2000 - 2009. 1725.
https://digitalcommons.fau.edu/etd_general_5/1725
Identifier
FADT369198
Comments
by Mustapha Mjit.|Thesis (M.S.C.S.)--Florida Atlantic University, 2009.|Includes bibliography.|Electronic reproduction. Boca Raton, Fla., 2009. Mode of access: World Wide Web.|by Mustapha Mjit.