Study on the Optimum Design of Pneumatic Conveying System Based on DNN

Abstract

Aiming at the problem that the traditional formula method is very complicated to calculate the pipeline pressure loss in the design process of pneumatic conveying system, the paper proposes a prediction model of pipeline pressure loss based on deep neural network (DNN). By supervising and analyzing the signals of flow parameters in the process of conveying, it can effectively extract the characteristics of signal by self-adaptive learning. The advantage of this prediction model is that it does not need to extract the characteristics of flow parameters signal in advance, and directly realizes the prediction of pipeline pressure loss end-to-end. This model avoids the complexity and signal loss in the process of artificially extracting parameter features, has higher stability and better prediction effect.