An Improved SVM Based Wind Turbine Multi-fault Detection Method.

A fault detection method bases on wind turbines (WTs) supervisory control and data acquisition (SCADA) is proposed, principal component analysis (PCA) was used to reduce the dimension of target features to 1-D, so that PCA output 1-D data can be used as label of support vector machine (SVM). Thus on the premise of not losing the prediction correctness, one model can detect the fault of 2 to 4 features, largely reduce the complexity of model building. Different experiments are present to show the effectiveness of the proposed method.