Diagnóstico de desequilíbrio de massa para rotores de aerogeradores utilizando máquina de vetores de suporte

Abstract

Condition monitoring systems (CMS) are essential to reduce costs in the wind energy sector. This paper proposes a method based on Support Vector Machine (SVM) to detect rotor mass imbalance for a multi-class problem, using the estimated speed as an input variable, obtained through a combination of electrical quantities (currents and voltages). In addition, with the aid of statistical tools, the proposed method allows the estimation of imbalance levels different from the classes proposed to the SVM. The angular position of the mass imbalance can also be obtained by analyzing the angular speed signal and the azimuth position of the wind turbine. A model of 1.5 MW wind turbine, three blades and with permanent magnet synchronous generator was considered, and a database was built numerically using the software Turbsim, FAST, and Simulink. From the database, the Power Spectral Density (PSD) technique was used to transform the input data from the time to the frequency domain. Then, the SVM algorithm and statistical analysis were used to classify the magnitude and the angular position of the imbalance. Different scenarios of mass imbalance were tested under different wind speeds and turbulence intensities. The results demonstrate the satisfactory performance of the proposed method.