Condition monitoring of electric machines is gaining interest in industry, because of increasing demand of fault tolerance machines. State-of-the-art diagnostic procedure are based on non-invasive signal processing of electrical signal that allow to detect fault signature at an incipient stage. Here, the use of Hilbert and Wavelet transform is investigated. Specifically, a theoretical analysis is presented that can be used to select the optimal wavelet, i.e. the decomposition level that corresponds to the maximum fault signature energy. Simulation results confirm the effectiveness of the proposed procedure, even under time-varying conditions.
Sintoni, M., Bellini, A., Forlivesi, D., Bianchini, C. (2021). Rotor Fault Detection of Induction Machines with Optimal Wavelet Transform [10.1109/WEMDCD51469.2021.9425651].
Rotor Fault Detection of Induction Machines with Optimal Wavelet Transform
Sintoni, Michele;Bellini, Alberto
;
2021
Abstract
Condition monitoring of electric machines is gaining interest in industry, because of increasing demand of fault tolerance machines. State-of-the-art diagnostic procedure are based on non-invasive signal processing of electrical signal that allow to detect fault signature at an incipient stage. Here, the use of Hilbert and Wavelet transform is investigated. Specifically, a theoretical analysis is presented that can be used to select the optimal wavelet, i.e. the decomposition level that corresponds to the maximum fault signature energy. Simulation results confirm the effectiveness of the proposed procedure, even under time-varying conditions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
