Fault Recognition of Wind Turbine Using EMD Analysis and FFT Classification

Abstract

This paper employs empirical mode decomposition (EMD) and fast Fourier transform (FFT) to analyze the oilleakage fault signal of the gearbox of wind turbines. K-nearest neighbors (KNN) is used on automatic fault recognition. First, both normal and faulty oil-leakage gearboxes are considered. Second, EMD is applied on analyzing the intrinsic mode function (IMF) of the current signals, and FFT is used to get the IMF spectrum. Finally, the features of the spectrum are extracted, and KNN is used on fault recognition of wind turbine gearboxes. The result indicates that it can effectively recognize the oil-leakage fault of gearboxes.

Time Scale Analysis of Precipitation Based on EMD Method in Xilin Gol

“…In 2010, Lu Jingwei [3] selected the Weihe River Basin as the research object to study the variation characteristics of hydrometeorological sequences by using the empirical modal decompositionm method and wavelet analysis method. In 2012, Deng-Fa Lin, Po-Hung Chenliyong [4] used empirical mode decomposition and fast Fourier transform to analyze the oil leakage fault signal of wind power gearbox, and performed FFT on the eigenmode function obtained by EMD decomposition. Find the IMF spectrum to identify the failure of the gearbox.…”