Fault Diagnosis Based on Wavelet Neural Network

As wind power generation is a complicated nonlinear time-varying system, it´s hard to extract effective fault feature. A novel arithmetic that combines modified LDB (Local Discriminant Basis) algorithm and SOM-BP network is proposed in this paper for fault diagnosis and location. First original fault features are extracted by improved LDB algorithm, then these fault features are mapped into a new feature space with high class separability via SOM (Self-Organizing Feature Map) nonlinearly transform, finally BP is used as a nonlinear classifier to implement fault diagnosis and location.