The Inter-turns Short Circuit Fault Detection based on External Leakage Flux Sensing and VMD-HHT Analytical Method for DFIG

The monitoring and analysis of the motor external leakage flux can experience various kinds of faults in stators and rotors, such as inter-turns short circuit fault, stator insulation failure, bearing fault, eccentricity and broken rotor bar/end-ring, etc., has been gaining more and more attention and research, due to its non-invasive, comparable to motor current signature analysis, and also more straightforward structure and lower cost, has been a modern and future trend as significant research work. However, for high-power wind turbines, especially, Doubly Fed Induction Generator (DFIG) is widely used at present, due to the harsh environment located, the external leakage flux signals of the generators are easily submerged by the strong noise background, which limits the practical engineering application of this technology. Aiming at the inter-turn short circuit fault of DFIG, this paper proposes a method for inter-turn short circuit fault feature extraction based on Variational Mode Decomposition and Hilbert-Huang Transform (VMD-HHT) method for the external magnetic flux leakage (MFL) of the generator. Through VMD decomposition of inter-turn short circuit fault signals, a series of intrinsic mode function (IMF) components are obtained. A comprehensive evaluation criterion of correlativity, kurtosis, and multi-scale permutation entropy was used to select the best IMF components with apparent features. The selected IMF components were analyzed by HHT. The fault features and the corresponding fault phenomenon were extracted by the VMD-HHT method. The experimental results show that the diagnosis method based on the VMD-HHT method can effectively extract the weak feature information from the external MFL signals and realize the fault feature extraction of inter-turn short circuit fault.