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.
Rotor fault detection of induction machines with optimal wavelet transform / Sintoni, M.; Bellini, A.; Forlivesi, D.; Bianchini, C.. - (2021), pp. 283-288. (Intervento presentato al convegno 2021 IEEE Workshop on Electrical Machines Design, Control and Diagnosis, WEMDCD 2021 tenutosi a ita nel 2021) [10.1109/WEMDCD51469.2021.9425651].
Rotor fault detection of induction machines with optimal wavelet transform
Bellini A.;Bianchini C.
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.Pubblicazioni consigliate
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