Research on Fault Diagnosis of Drive Train in Wind Turbine Based on EMD and LSSVM

Abstract

Fault feature extraction method based on Empirical Mode Decomposition (EMD) and fault diagnosis model based on Least Squares Support Vector Machines (LSSVM) were proposed after typical faults in drive train for wind turbines being analyzed. An experiment was designed to verify the validity of feature extraction method and the intelligent diagnosis model. The results showed that EMD can effectively extract fault characteristics of the drive train in wind turbines, the classification speed and diagnosis accuracy of LSSVM classifier based on radial basis function are better than the SVM, BPNN and other classifiers which are commonly used in practice.