A Fault Diagnosis Method for Power Transformer Based on Multiclass Multiple-kernel Learning Support Vector Machine

A novel support vector machine(SVM),i.e.multiclass multiple-kernel learning support vector machine(MMKL-SVM),for the fault diagnosis of power transformers is proposed in this paper.Unlike traditional SVM that may fail under some circumstances,the fault diagnosis method based on MMKL-SVM has some good theoretical properties,e.g.it only deals with a simple objective function,and the classification results can be obtained by direct calculation on the basis of a simple decision function;it can conduct calculation with an optimal kernel function composed of linear combinations of basic kernels,further boosting the overall performance;the solutions for it can be efficiently gained by iteratively solving two convex optimization functions with a low computation cost and high speed.Diagnosis test results show that the MMKL-SVM method has high classification accuracy,which proves its effectiveness and usefulness.