Rotor fault diagnosis techniques developed for induction machines (IMs) are classically based on current spectral analysis (CSA). For the case of rotor asymmetry in Wound-Rotor Induction Machine (WRIM), the magnitude of the negative sequence component at -sf of the rotor current space-vector is commonly monitored in order to quantify its contribution. Nevertheless, CSA still has some limitations. In fact, under speed-varying conditions, an effective frequency analysis using the Fast Fourier Transform (FFT) algorithm cannot be applied, since slip is varying, and then the magnitude of the rotor fault component -sf is also varying. In the present paper, a new approach based on Voltage Space vector Signature Analysis (VSSA) is presented for accurate rotor High Resistance Connection (HRC) fault detection in WRIM under speed-varying operating conditions. The reliability of the presented diagnosis technique is validated by numerical simulations. The proposed technique can be easily implemented in the control platform of any modern wind power plants, for online rotor fault monitoring.

Accurate rotor fault detection in doubly-fed Wound-Rotor Induction Machine

Tani, A.;Rossi, C.;Casadei, D.;
2017

Abstract

Rotor fault diagnosis techniques developed for induction machines (IMs) are classically based on current spectral analysis (CSA). For the case of rotor asymmetry in Wound-Rotor Induction Machine (WRIM), the magnitude of the negative sequence component at -sf of the rotor current space-vector is commonly monitored in order to quantify its contribution. Nevertheless, CSA still has some limitations. In fact, under speed-varying conditions, an effective frequency analysis using the Fast Fourier Transform (FFT) algorithm cannot be applied, since slip is varying, and then the magnitude of the rotor fault component -sf is also varying. In the present paper, a new approach based on Voltage Space vector Signature Analysis (VSSA) is presented for accurate rotor High Resistance Connection (HRC) fault detection in WRIM under speed-varying operating conditions. The reliability of the presented diagnosis technique is validated by numerical simulations. The proposed technique can be easily implemented in the control platform of any modern wind power plants, for online rotor fault monitoring.
2017 6th International Conference on Clean Electrical Power: Renewable Energy Resources Impact, ICCEP 2017
756
760
Gritli, Y.; Tani, A.; Rossi, C.; Casadei, D.; Filippetti, F.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/625631
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