In order to solve the problem of consuming too much calculation time and low rate of searching in the construction process of multi-class classification of support vector machines (SVM), the fine global search performance of particle swarm is applied to the optimization of decision tree in order to construct a diverse classifier and ultimately achieve more effective multi-value classification for SVM.The improved SVM constructing method is proved more effective and accurate while being applied to gearbox fault diagnosis.