Abstract: To solve the problem that some important parameters in chemical process are difficult to measure on-line, a soft sensor modeling method based on time series neural network for multirate system is proposed. A dynamic interpolation neural network (DINN) is established according to the proposed new method, and the enhanced particle swarm optimization (EPSO) algorithm is applied for the network parameter optimization. Efficiency of the proposed method has then been verified through experiments, the online estimate of output variables has been realized , and the training and generalization properties of the network have been analyzed. The proposed model based on EPSO-DINN has been proved having a better performance than normal BPNN.