用MATLAB神经网络预测气力输送过程物料破碎率

Prediction of Material Breaking Rate during Pneumatic Conveying with MATLAB Neural Network

物料在气力输送过程中的破碎率大小,是评判气力输送系统及输送工艺优劣的重要参数之一。利用MATLAB语言,将炭黑气力输送系统各位置的压力数据输入BP神经网络,用训练好的网络模型进行仿真,对炭黑的破碎率进行了预测。与实验结果对比,采用BP神经网络对炭黑破碎率的预测具有比较高的精确度,可对气力输送系统的优化设计以及输送工艺参数的优化选取提供指导。

The breaking rate of materials during pneumatic conveying is one of the key performance indicators of the pneumatic conveying system and the conveying technique.The breaking rate of carbon black was predicted through simulation with a well trained network model by entering pressure data from each location of the pneumatic conveying system of carbon black to the BP neural network using MATLAB language.Compared with the test result,prediction of the carbon black breaking rate with BP neural network offers a high accuracy,which can provide guidance for optimized design of the pneumatic conveying system and the optimized selection of conveying technical parameters.