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Networking of Distributed Sensors for Proactive Condition Monitoring of Wind Turbines

Reference Number
EP/C547594/1
Title
Networking of Distributed Sensors for Proactive Condition Monitoring of Wind Turbines
Status
Completed
Energy Categories
Renewable Energy Sources(Wind Energy)
Research Types
Basic and strategic applied research
Applied Research and Development
Science and Technology Fields
ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering)
UKERC Cross Cutting Characterisation
Not Cross-cutting
Principal Investigator
Professor I Andonovic
Electronic and Electrical Engineering
University of Strathclyde
Award Type
Standard
Funding Source
EPSRC
Start Date
01 October 2005
End Date
30 September 2008
Duration
36 months
Total Grant Value
£440,292
Industrial Sectors
Info. & commun. Technol.
Region
Scotland
Programme
Information & Communication Technology
Investigators
Principal Investigator
Professor I Andonovic, Electronic and Electrical Engineering, University of Strathclyde
Other Investigator
Dr D Harle, Electronic and Electrical Engineering, University of Strathclyde
Dr S McArthur, Electronic and Electrical Engineering, University of Strathclyde
Professor J McDonald, Electronic and Electrical Engineering, University of Strathclyde
Professor A McNab, Electronic and Electrical Engineering, University of Strathclyde
Recognised Researcher
Prof GA Ault, Electronic and Electrical Engineering, University of Strathclyde
Industrial Collaborator
Project Contact, Scottish Power Ltd
Project Contact, Agilent Technologies UK Ltd
Project Contact, Moog Insensys Ltd
Project Contact, MESL Microwave Limited
Project Contact, National Engineering Laboratory
Project Contact, Institute for Space Astrophysics and Planetology
Web Site
Objectives
NB This grant is linked to EP/C014790/1 and EP/C014804/1
Abstract
This project addresses the investigation and demonstration of techniques that enable proactive automated control and management of sensor arrays, focusing in particular on applications of sensor arrays in the operation and management of wind farms. The research will identify desirable proactive behaviours and propose novel nature-inspired algorithms to deliver them. It will also explore mechanisms that facilitate the use of proactive control and management software including a) a policy drivenmanagement infrastructure that will use high level user goals to constrain the instrument level proactive behaviours, b) a parallel platform that supports appropriate observation, communication and actuation, and c) a lightweight, resilient peer to peer wireless communications architecture. The project will integrate the results of this research into a large scale demonstration intended for deployment at a hilltop windfarm.
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Added to Database
13/08/07