Title :
Efficient diagnostic condition monitoring for industrial wind turbines
Author :
Hajiabady, S. ; Kerkyras, S. ; Hillmansen, Stuart ; Tricoli, P. ; Papaelias, M.
Author_Institution :
Birmingham Centre for Railway Res. & Educ., Univ. of Birmingham, Birmingham, UK
Abstract :
The drive-train and power electronics are critical for the operation of industrial wind turbines. Faults developing in these components can result in long downtime and expensive repair costs, particularly when offshore wind farms are concerned. Effective condition monitoring (CM) of these components can result in significant savings for wind farm operators and contribute to a substantial improvement of the operational reliability of wind turbines. This paper considers a novel modular CM system capable of diagnosing faults in the gearbox. The data analysis methodology and the key results arising from measurements on actual industrial wind turbines are also presented.
Keywords :
condition monitoring; data analysis; offshore installations; power system faults; power system reliability; wind turbines; condition monitoring; data analysis methodology; drivetrain; gearbox; industrial wind turbines; offshore wind farms; power electronics; wind farm operators; condition monitoring; diagnosis; wind turbine;
Conference_Titel :
Renewable Power Generation Conference (RPG 2014), 3rd
Conference_Location :
Naples
DOI :
10.1049/cp.2014.0932