Fault Diagnosis and Application Based on SOM Neural Network

Abstract

In the actual demand of traction, the field of fault diagnosis technology applications is more and more widely. SOM (Self-organizing Feature Map) neural network is an unsupervised competitive learning; it uses a self-learning mode without teachers, without the need for training or learning process in advance to specify the training input data belongs to the category. Based on the characteristics of SOM neural network, a typical fault data is used to simulate the fault diagnosis and the simulation results show that the proposed neural network can accomplish the fault diagnosis task well.