中国电机工程学报2012，Vol.32Issue(5)：54-60,7.
基于PSO-BP神经网络的水焦浆管道压降预测
Prediction of Pressure Drop of Coke Water Slurry Flowing in Pipeline by PSO-BP Neural Network
摘要
Abstract
Experimental researches were carried out on a small-scale slurry transportation system to investigate resistance properties of coke water slurry flowing in pipes with four different diameters.There exists wall slip behavior when coke water slurry flows in the pipes,which could cause drag reduction.Therefore,it is necessary to correct wall slip behavior to predict pressure drop of coke water slurry.An artificial neural networks improved by PSO（particle swarm optimization） with five parameters in input layer was constructed to predict the pressure drop of coke water slurry flowing in the pipeline.Then pressure drop was predicted by artificial neural network and results were compared with the experimental value.The results show that PSO-BP artificial neural network has a good ability in predicting the pressure drop of coke water slurry flowing in the pipe.The error between the predicted value and experimental value is small and the largest error is no more than 10%.关键词
水焦浆/压降/壁面滑移/神经网络/粒子群优化算法Key words
coke water slurry/pressure drop/wall slip/artificial neural network/particle swarm optimization（PSO）分类
能源科技引用本文复制引用
马修元,段钰锋,刘猛,李华锋..基于PSO-BP神经网络的水焦浆管道压降预测[J].中国电机工程学报,2012,32(5):54-60,7.基金项目
国家重点基础研究发展计划项目(973项目)(2010CB227001) （973项目）
国家重点实验室开放基金资助(ZJUCEU2010002)~~ （ZJUCEU2010002）
