Open AccessSVD filtering and TLS‐ESPRIT algorithm based on stator fault characteristic detection of doubly‐fed induction generator
Author(s) -
Xu Boqiang,
Zheng Zehui
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.9265
Subject(s) - stator , signal (programming language) , singular value decomposition , algorithm , control theory (sociology) , rotor (electric) , fault detection and isolation , computer science , fault (geology) , engineering , artificial intelligence , electrical engineering , control (management) , seismology , geology , actuator , programming language
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