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Mining and fusing data for ocean turbine condition monitoring
Title
Mining and fusing data for ocean turbine condition monitoring.
Creator
Duhaney, Janell A., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
An ocean turbine extarcts the kinetic energy from ocean currents to generate electricity. Machine Condition Monitoring (MCM) / Prognostic Health Monitoring (PHM) systems allow for self-checking and automated fault detection, and are integral in the construction of a highly reliable ocean turbine. MCM/PHM systems enable real time health assessment, prognostics and advisory generation by interpreting data from sensors installed on the machine being monitored. To effectively utilize sensor...
Show moreAn ocean turbine extarcts the kinetic energy from ocean currents to generate electricity. Machine Condition Monitoring (MCM) / Prognostic Health Monitoring (PHM) systems allow for self-checking and automated fault detection, and are integral in the construction of a highly reliable ocean turbine. MCM/PHM systems enable real time health assessment, prognostics and advisory generation by interpreting data from sensors installed on the machine being monitored. To effectively utilize sensor readings for determining the health of individual components, macro-components and the overall system, these measurements must somehow be combined or integrated to form a holistic picture. The process used to perform this combination is called data fusion. Data mining and machine learning techniques allow for the analysis of these sensor signals, any maintenance history and other available information (like expert knowledge) to automate decision making and other such processes within MCM/PHM systems. ... This dissertation proposes an MCM/PHM software architecture employing those techniques which were determined from the experiments to be ideal for this application. Our work also offers a data fusion framework applicable to ocean machinery MCM/PHM. Finally, it presents a software tool for monitoring ocean turbines and other submerged vessels, implemented according to industry standards.
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Date Issued
2012
PURL
http://purl.flvc.org/FAU/3358556
Subject Headings
Marine turbines, Mathematical models, Fluid dynamics, Data mining, Machine learning, Multisensor data fusion
Format
Document (PDF)
Model analysis of a mooring system for an ocean current turbine testing platform
Title
Model analysis of a mooring system for an ocean current turbine testing platform.
Creator
Cribbs, Allison Rose., College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description
In response to Florida's growing energy needs and drive to develop renewable power, Florida Atlantic Universitys Center for Ocean Energy Technology (COET) plans to moor a 20 kW test turbine in the Florida Current. No permanent mooring systems for deepwater hydrokinetic turbines have been constructed and deployed, therefore little if anything is known about the performance of these moorings. To investigate this proposed mooring system, a numeric model is developed and then used to predict the...
Show moreIn response to Florida's growing energy needs and drive to develop renewable power, Florida Atlantic Universitys Center for Ocean Energy Technology (COET) plans to moor a 20 kW test turbine in the Florida Current. No permanent mooring systems for deepwater hydrokinetic turbines have been constructed and deployed, therefore little if anything is known about the performance of these moorings. To investigate this proposed mooring system, a numeric model is developed and then used to predict the static and dynamic behavior of the mooring system and attachments. The model has been created in OrcaFlex and includes two surface buoys and an operating turbine. Anchor chain at the end of the mooring line develops a catenary, providing compliance. Wind, wave, and current models are used to represent the environmental conditions the system is expected to experience and model the dynamic effects on the system. The model is then used to analyze various components of the system. The results identify that a mooring attachment point 1.25 m forward of the center of gravity on the mooring buoy is ideal, and that the OCDP and turbine tether lengths should be no shorter than 25 and 44 m, respectively. Analysis performed for the full system identify that the addition of the floats decreases the tension at the MTB attachment location by 26.5 to 29.5% for minimum current, and 0.10 to 0.31% for maximum current conditions.
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Date Issued
2010
PURL
http://purl.flvc.org/FAU/2974432
Subject Headings
Marine turbines, Mathematical models, Structural dynamics, Rotors, Design and construction, Offshore structures, Testing
Format
Document (PDF)
Finite Element Modeling and Fatigue Analysis of Composite Turbine Blades under Random Ocean Current and Turbulence
Title
Finite Element Modeling and Fatigue Analysis of Composite Turbine Blades under Random Ocean Current and Turbulence.
Creator
Canino, Marco M., Mahfuz, Hassan, Florida Atlantic University, College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description
Several modifications have been implemented to numerical simulation codes based on blade element momentum theory (BEMT), for application to the design of ocean current turbine (OCT) blades. The modifications were applied in terms of section modulus and include adjustments due to core inclusion, buoyancy, and added mass. Hydrodynamic loads and mode shapes were calculated using the modified BEMT based analysis tools. A 3D model of the blade was developed using SolidWorks. The model was...
Show moreSeveral modifications have been implemented to numerical simulation codes based on blade element momentum theory (BEMT), for application to the design of ocean current turbine (OCT) blades. The modifications were applied in terms of section modulus and include adjustments due to core inclusion, buoyancy, and added mass. Hydrodynamic loads and mode shapes were calculated using the modified BEMT based analysis tools. A 3D model of the blade was developed using SolidWorks. The model was integrated with ANSYS and several loading scenarios, calculated from the modified simulation tools, were applied. A complete stress and failure analysis was then performed. Additionally, the rainflow counting method was used on ocean current velocity data to determine the loading histogram for fatigue analysis. A constant life diagram and cumulative fatigue damage model were used to predict the OCT blade life. Due to a critical area of fatigue failure being found in the blade adhesive joint, a statistical analysis was performed on experimental adhesive joint data.
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Date Issued
2016
PURL
http://purl.flvc.org/fau/fd/FA00004727, http://purl.flvc.org/fau/fd/FA00004727
Subject Headings
Composite materials -- Fatigue, Finite element method, Fluid dynamics, Marine turbines -- Mathematical models, Ocean wave power, Structural dynamics
Format
Document (PDF)

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