RAILWAY VEHICLES PANTOGRAPH FAULT DIAGNOSIS BASED ON VARIATIONAL MODE DECOMPOSITION DISPERSION ENTROPY AND SVM

Abstract

In order to improve the fault diagnosis accuracy of railway vehicles pantograph, a fault diagnosis method of pantograph based on variational mode decomposition（VMD） dispersion entropy（DE） and support vector machine（SVM） was proposed in this paper. Firstly, VMD was used as the fault signal decomposition method to realized pantograph signal in different states adaptively decomposition, and obtained several intrinsic mode functions（IMF）. Secondly, DE was used as feature extration method to calculated each IMF DE value and obtained the fault feature vectors. Finally, SVM was used as pattern recgnition method to identified the fault features and the diagnosis results are obtained. An example of pantograph fault diagnosis shows the effectiveness of the method.

Keywords

• Variational modal decomposition;Dispersion entropy;Support vector machine;Pantograph;Fault diagnosis