Monitoring

On August 5, 2010 the U.S. Department of Energy (DOE) has designated the Center for Ocean Energy Technology (COET) at Florida Atlantic University (FAU) as a national center for ocean energy research and development. Their focus is the research and development of open-ocean current systems and associated infrastructure needed to development and testing prototypes. The generation of power is achieved by using a specialized electric generator with a rotor called a turbine. As with all machines, the turbines will need maintenance and replacement as they near the end of their lifecycle. This prognostic health monitoring (PHM) requires data to be collected, stored, and analyzed in order to maximize the lifespan, reduce downtime and predict when failure is eminent. This thesis explores the use of a data gateway which will separate high level software with low level hardware including sensors and actuators. The gateway will v standardize and store the data collected from various sensors with different speeds, formats, and interfaces allowing an easy and uniform transition to a database system for analysis.

On August 5, 2010 the U.S. Department of Energy (DOE) has designated the Center for Ocean Energy Technology (COET) at Florida Atlantic University (FAU) as a national center for ocean energy research and development of prototypes for open-ocean power generation. Maintenance on ocean-based machinery can be very costly. To avoid unnecessary maintenance it is necessary to monitor the condition of each machine in order to predict problems. This kind of prognostic health monitoring (PHM) requires a condition-based maintenance (CBM) system that supports diagnostic and prognostic analysis of large amounts of data. Research in this field led to the creation of ISO13374 and the development of a standard open-architecture for machine condition monitoring. This thesis explores an implementation of such a system for ocean-based machinery using this framework and current open-standard technologies.

Anecdotal accounts of manatees congregating in the Harbor Branch channel have been reported by staff scientists at the Harbor Branch Oceanographic Institute for over three decades. The main goals of this study were to identify individual manatees using photo-identification techniques and collect baseline data on manatee abundance and environmental parameters. During the primary study period (summer 2009), I identified 31 distinct manatees at Harbor Branch. Four manatees were matched with the statewide Manatee Individual Photo-identification System database. I observed the highest abundance of manatees in the small boats marina, suggesting that this location is preferential manatee habitat. Water temperature at the two deepest depths measured (0.6 m and 1.50 m) were the only two significantly different environmental parameters influencing the number of manatees present. The results of this study provide evidence for the Harbor Branch channel as an important manatee habitat.