Abstract:
<p>The objectives for this project are: <bl> <li>Develop technology which is capable of cost effectively providing prognostic information about the mechanical health of a wind turbine.</li> <li>Install the technology on a wind turbine, and establish normal "signatures" for the mechanical components, and their variation with operating conditions.</li> <li>Conduct an in-field trial to establish the variability of the data from different wind turbines, and any seasonal variability in the data.</li> <li>Demonstrate the use of Artificial Intelligence (AI) /model-based techniques to extract prognostic information from the data.</li> </bl></br> <p>This project aims to demonstrate the ability to monitor wind turbine health using inherently low cost and robust instrumentation, through the development and installation of a trial system on land-based wind turbines, and reviewing and analysing the data over a period of up to a year.</p> This profile contains information on the project's: <bl> <li>Objectives</li> <li>Summary</li> <li>Contractor</li> <li>Collaborators</li> <li>Cost</li> <li>Duration</li> </bl>Publication Year:
2005
Publisher:
Department of Trade and Industry
DOI:
No DOI minted
Author(s):
DTI
Energy Category
Language:
English
File Type:
application/pdf
File Size:
182546 B
Rights:
Rights not recorded
Rights Overview:
Rights are not recorded within the edc, check the data source for details
Further information:
N/A
Region:
United Kingdom
Related Dataset(s):
No related datasets
Related Project(s):
Development of Prognostic /Health Management (PHM) Technologies for Wind Turbines
Related Publications(s):
No related publications