用人工神经网络法研究管道中浆体摩阻损失  

STUDY ON FRICTIONAL LOSS OF SLURRY IN PIPE BY ARCTIFICIAL NEURAL NETWORK

作　　者：韩旭[1] 张奇志[1] 佟庆理 

机构地区：[1]东北大学机械工程学院

出　　处：《矿冶工程》1997年第1期5-8,共4页Mining and Metallurgical Engineering

摘　　要：对铜铅锌铁尾矿、粉煤灰和氧化铝工业赤泥三种浆体的摩阻损失进行了试验研究。在试验研究结果和前人工作基础上，利用人工神经网络法对管道内浆体摩阻损失进行拟合和预测。结果表明，预测浆体摩阻损失与实测浆体摩阻损失相吻合。Experimental study is made for the frictional loss of three kinds of slurries, such as copper lead zin iron tailings, coal ash and so on. Based on experimental results and previous works, frictional loss of slurry in pipe has been simulated and predicated by artificial neural network. The results show that the predicted frictional losses are in agreement with measured ones.

关 键 词：摩阻损失 浆体输送 人工神经网络 管道 

分 类 号：TB126[理学—工程力学]