噪声与振动控制2018，Vol.38Issue(1)：220-224,5.DOI:10.3969/j.issn.1006-1355.2018.01.043
基于声发射的气力输送颗粒相质量流量监测
Monitoring of Particle Mass Flow Rate in Pneumatic Conveying Based on Acoustic Emission
摘要
Abstract
The particle mass flow rate in pneumatic conveying is one of the important parameters to be monitored during the operation.The real time on-line measurement can be realized by using the acoustic emission signals to monitoring the particle mass flow rate.In this paper,by using the Ensemble Empirical Mode Decomposition(EEMD)algorithm,which can decompose the signals based on the original signal,and the artificial neural network,which has the excellent nonlinear mapping ability, an EEMD and BP neural network combined mass flow measurement model is established. The experimental data samples are used to train the network to achieve the mass flow online estimation.It is found that result of the joint model is in good agreement with the experimental result.This work provides a simple and reliable method for the on-line measurement of particle mass rate flow in pneumatic conveying.关键词
声学/气力输送/EEMD/神经网络/声发射/质量流量Key words
acoustics/pneumatic conveying/EEMD/neural network/acoustic emission/mass flow rate分类
机械制造引用本文复制引用
安连锁,刘伟龙,魏萌,沈国清,张世平..基于声发射的气力输送颗粒相质量流量监测[J].噪声与振动控制,2018,38(1):220-224,5.基金项目
中央高校基本科研业务费专项资金资助项目(2017ZZD001) （2017ZZD001）
中央高校基本科研业务费专项资金资助项目(2015XS83) （2015XS83）
