Study of Fault Diagnosis for Condenser Based on Support Vector Machine

Condenser\'s working process and fault mechanism are analyzed,whose typical fault concourses,symptom concourses and typical fault feature vectors are established.A fault diagnosis model is set up based on support vector machine method.The effective of this method has been demonstrated by specific sample calculations.A comparison with a neural network model has shown that the support vector machine method is superior to the neural network method in terms of calculation results,generalization ability and efficiency under the condition of small quantity samples.When a relatively small number of diagnosis samples are involved,the above method may provide a new approach for creating an intelligent system of highly practical value for the condition monitoring and fault diagnosis of condenser.