Open AccessStudy on detection of blade imbalance for DFIG WTS based on spectrum analysis of Hilbert modulus
Author(s) -
Jixing Qiu,
Guodong Xu,
Junbing Tao,
Jing Yang
Publication year - 2017
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2017.0548
Subject(s) - stator , doubly fed electric machine , control theory (sociology) , harmonics , induction generator , computer science , signal (programming language) , generator (circuit theory) , fault (geology) , fault detection and isolation , blade (archaeology) , harmonic , wind power , physics , acoustics , structural engineering , power (physics) , engineering , ac power , mechanical engineering , voltage , artificial intelligence , electrical engineering , control (management) , quantum mechanics , seismology , actuator , programming language , geology
To detect the impellor imbalance of double fed induction generator (DFIG) wind turbines (WTs), a spectrum analysis of Hilbert modulus based on stator current signal has been proposed. The current‐based detection method is cost‐effective and valuable in engineering applications. According to the models of DFIG WTs and coordinate transformations, this study presents the expressions of stator current in three‐phase static coordinates under imbalance condition. In addition, the fault frequency ( f 1 ± f m ) is derived evidently. The blade imbalance fault can be diagnosed by extracting f m (shaft rotating frequency) component based on the Hilbert transformation. Furthermore, the detecting process only works in constant speed stage and f m , which is also called 1P frequency, is invariable. Experimental tests on commercial 1.5 MW DFIG WTs have been taken for verifying the detecting algorithm proposed above. Finally, it is effective to recognise the blade imbalance with the advantages of cost and system reliability.