Toward an online strategy for mechanical failures diagnostics inside the wind turbine generators based on spectral analysis

Abstract

Mechanical faults in wind turbine generators lead to a huge problems of breaking electricity production, increase the maintenance cost and can damage the wind turbine generator, which caught fire in the nacelle. Gearbox installed in the nacelle is the important component in wind turbine, it composed by shafts bearings and gearings. Always bearings and gearings failures are related together. Therefore, to control these rotating components we need to analysis their vibration signature. This work was done with Tunisian Electricity and Gas Company (STEG) it’s about mechanical failures diagnostics which are based on three temporal vibration signals which are made by three sensors installed also in three positions axial, vertical, and horizontal. In this work we present a Fast Fourier Transform which is applied on raw mechanical vibration signals by the vibration department of STEG, which are compared with a new strategy of envelope analysis is commonly used to obtain the mechanical faults harmonics from the envelope signal spectrum analysis and has shown a more suitable results of diagnostics which is applied on the same data sets from Fast Fourier Transform. In this work, we illustrate a squared envelope based on spectral kurtosis approach to determine optimum envelope analysis parameters including the filtering band and center frequency through a short time Fourier transform. This method proves a better diagnosis results using real vibration data set from vibration department of STEG.