Current spectrum analysis for induction machine fault detection

Abstract

U ovom diplomskom radu je opisana jedna od najznacajnih on line metoda za di- jagnostiku kvara motora (MCSA). Ova metoda je bazirana na snimanju statorskih struja i spektralnoj analizi putem brze Fourierove transformacije. Fourierov spektar moze pomoci pri odredivanju karakteristicnih frekvencija kvarova. Promatrajuci ispravan motor u odnosu na kvarno stanje, moze se zakljuciti o kakvom kvaru se radi. Pri snimanju struja, motor treba biti opterecen teretom od barem 70% nazivnog momenta. Na temelju rezultata, kreiran je algoritam koji je baziran na omjerima energije signala i koji odlucuje o tipu kvara.One of the most signicant on line diagnostic methods for fault condition of induction motor (MCSA) has been described in this master thesis. This method is based on recording stator currents and spectral analysis through fast Fourier transformation. The Fourier spectrum can help to determine the characteristic fault frequencies. Considering a healthy motor in relation to unhealthy motor, it can be concluded about type of failure state. When recording the current, the motor must be loaded with a load of at least 70 % of the nominal torque. Based on the results, an algorithm, which is based on the signal energy ratios and decides about type of failure, was created