Maintenance management of wind turbines structures via MFCs and wavelet transforms

This paper introduces a novel Fault Detection and Diagnosis method based on the wavelet transform to detect defects on the tower of a wind turbine. 24 Macro-Fiber Composite transducers have been placed to send and collect ultrasound signals. The data have been converted into voltage and analyzed by the wavelet transforms. Wavelet transform detects particular characteristics according to the shape or amplitude, and lead to diagnose imperfections in towers. Regarding to the wind turbines maintenance management, a large number of publications can be found focused on blades, mechanical, electrical/electronic devices, etc. However this trend is not extended to the wind turbine towers, and the development of their maintenance systems is not widespread yet. The results from this paper lead to acquire an early indication of structural or mechanical problems and it anticipates to catastrophic failures. It also allows a better preventive and predictive maintenance in wind turbines.