SVD filtering and TLS-ESPRIT algorithm based on stator fault characteristic detection of doubly-fed induction generator

Abstract

This study proposes a novel method for detecting faults in the stator of the doubly-fed wind turbines based on the combination of singular value decomposition (SVD) filtering and least-squares parameter invariant signal technique (TLS-ESPRIT). The stator current signal and rotor current signal are simulated in the form of stator inter-turn short-circuit fault, and TLS-ESPRIT performance test is carried out. The results show that TLS-ESPRIT still has a high-frequency resolution for a short-time signal with high-frequency resolution and can accurately estimate the frequency of each part of stator current. This method can effectively shorten the sampling signal's tempo, the performance of its parameter estimation is also superior.a

Keywords

• rotors
• stators
• asynchronous generators
• fault diagnosis
• singular value decomposition
• parameter estimation
• wind turbines
• doubly-fed induction generator
• stator fault characteristic detection
• tls-esprit algorithm
• svd filtering
• sampling signal
• short-time signal
• high-frequency resolution
• tls-esprit performance test
• stator inter-turn short-circuit fault
• rotor current signal
• stator current signal
• least-squares parameter invariant signal technique
• doubly-fed wind turbines