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The purpose of this project was to investigate the most appropriate technology to operate and maintain offshore wind farms so that the implemented technology allows the optimization of the Operation & Maintenance looking for maximum profitability. 2007 - 2011


CENIT EOLIA Project Features:


Heuristic models of wind turbine components.


Heuristic knowledge of the process was used to make a qualitative assessment of the state of various elements in the system. As a result a condition monitoring of the system elements is obtained and its tendency to failure.


Analytical models of wind turbine components.


Monitoring, fault detection and diagnosis is particularly difficult in complex systems, also of the variable operating time, this is the reason that traditional techniques such as vibration monitoring, thermal analysis, etc., can not provide a proper fault diagnosis. To improve existing detection systems failures, the group developed more detailed analytical models, which take into account the peculiarities of offshore wind turbines.


Expert system data integration, diagnosis and decision support.


Once identified and classified the critical elements, and realized the heuristic and analytic treatment to detect failures, it is necessary to integrate the information provided by each fault detection modules, to establish a state analysis of each component, a fault diagnosis and a fault trends that subsequently can be integrated into a maintenance management system and decision support.


  The integration of the results of the heuristic and analytical treatment is performed by an expert system being this technique more effective in implementation and integration of the various tasks of monitoring and planning of complex industrial processes. 

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