The development of intelligent fault diagnosis is restricted by the shortage of the fault sample

in this paper

a new method-support vector machine is proposed

and then Genetic Algorithms is used to optimize the important parameters-penalty factor C and kernel parameter γ.In this paper

the engine fault diagnosis is regarded as training samples.The training samples realized dimension reduction and decorrelation by principal component analysis.Support vector machine model of engine fault diagnosis ...