A fault diagnosis method for three-phase rectifiers

For fault feature extraction and fault identification, a novel method based on principal component analysis and support vector machines were presented for fault diagnosis of three-phase rectifiers, in which the principal component analysis of fault signal is used to extract the features corresponding to various fault, then fault types are identified through the pattern recognition classifier based on support vector machines. The simulation result of fault diagnosis of a thyristor in a three-phase full-bridge controlled rectifier showed that the method can make an accurate identification of fault types as well as the location of the fault elements for power electronics circuits, and it has an excellent performance for noise robustness and calculation complexity. Therefore, it is quite practically valuable in the solution to the fault problems for power electronics rectifiers.