Aiming at the problem that the classification performance of support vector machine (SVM) is greatly affected by its own parameter selection,A method to optimize SVM based on Sparrow Search Algorithm (SSA) was proposed .The sparrow search algorithm (SSA) was used to optimize the penalty factor C and the kernel function g of the support vector machine, and the SSA-SVM rolling bearing fault diagnosis model was constructed.The results show that for several common faults of rolling bearings, the test accuracy of the SSA-SVM diagnostic model is 96.67%, which is 3.34% and 1.67% higher than the traditional GA-SVM and PSO-SVM diagnostic models, and the convergence speed is faster,It can be effectively applied to fault diagnosis.