Wind turbines (WT) maintenance management is in continuous development to improve the reliability, availability, maintainability and safety (RAMS) of WTs, and to achieve time and cost reductions. The optimisation of the operation reliability involves the supervisory control and data acquisition to guarantee correct levels of RAMS. A fault detection and diagnosis methodology is proposed for large-scale industrial WTs. The method applies the wavelet and Fourier analysis to vibration signals. A number of turbines (up to 3) of the same type will be instrumented in the same wind farm. The data collected from the individual turbines will be fused and analysed together in order to determine the overall reliability of this particular wind farm and wind turbine type. It is expected that data fusion will allow a significant improvement in overall reliability since the value of the information gained from the various condition monitoring systems will be enhanced. Effort will also focus on the successful application of dependable embedded computer systems for the reliable implementation of wind turbine condition monitoring and control technologies.