Abstract:In order to predict the wear of mechanical equipment accurately,Volterra series prediction model based on improved particle swarm optimization(PSO) algorithm was put forward.This prediction method firstly establishes the Volterra series model according to the nature of the Volterra series,then establishes Volterra series prediction model by optimizing the parameters of the model with the improved PSO algorithm.The wear experimental data of the bearing steel gear specimen was used to establish the prediction model,and the wear of the bearing steel gear was predicted.The prediction results show that,in comparison with Volterra model based on PSO algorithm,polynomial model,AR model,RBF neural network model and BP neural network model,the proposed model has simpler structure and higher prediction precision,which has certain practicability.