The vibration analysis of operational response data from a 2.3 MW wind turbine is presented. Vibration signals were acquired for two unique environmental conditions with an accelerometer mounted in the turbine tower. A Daubechies 6th order (db6) wavelet was used to perform a 12-level discrete wavelet transform (DWT) revealing trends and similarities within the signals. Full operation signals were segmented into start up and steady state periods. Analysis of turbine start up revealed a common ramping of low frequency energy on the order of rotor rotational frequency. DWT plots were also utilized to reveal high-energy response features related to the mechanical start up of the turbine. Analysis of steady state signals revealed distinct low frequency periodicity evident in the 11th (0.1776Hz) and 12th (0.0888 Hz) decomposition levels. The analysis technique performed shows promise for potential integration into comprehensive structural health monitoring schemes designed to reduce downtime and improve the reliability of commercial wind turbines.
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