IMS 2004 (Intelligent Maintenance Systems - International Conference 4th), Arles (France). 15-16 Julio 2004
Summary:
The use of wind is one of the most attractive sources of energy at the present moment, as can be seen by the growing installation of windfarms all over the world. Windturbines are relatively young machines where the application of a correct maintenance strategy would be very important for the protection of their future life, productivity and profitability. This paper presents the architecture of a novel predictive maintenance system based on artificial intelligent techniques and applied to windturbines. Its main goal is to find the most appropriate time to carry out the needed maintenance actions from a component health condition and an incipient failure diagnosis perspective. Therefore, this intelligent system optimizes and dynamically adapts a maintenance calendar for the wind turbine that it is monitoring, according to the real needs and operating life of the wind turbine as well as other technical and economical criteria. Therefore, this philosophy is different from the traditional scheduled maintenance plan based on fixed time intervals following the manufacturer criteria which do not focus on the real and local operation conditions of the the windturbine.
Keywords: Predictive maintenance, maintenance effectiveness, health condition, diagnosis artificial intelligence
Publication date: July 2004.
Citation:
García, M., Sanz-Bobi, M.A., del Pico, J., Intelligent system for predictive maintenance scheduling and effectiveness measurement applied to Wwndturbines, IMS 2004 (Intelligent Maintenance Systems - International Conference 4th), Arles (France). 15-16 July 2004.
IIT-04-018A
