基于声发射的管道内气固两相流颗粒相含量测量

发布时间：2018-03-30 01:31

本文选题：气固两相流　切入点：颗粒相含量　出处：《热力发电》2017年11期

【摘要】：为了实现管道内气固两相流颗粒相含量的在线测量,通过安装在管道截面网状结构上的传感器对管道内不同含量的气固两相流的声发射信号进行采集,通过集合经验模分解(EEMD)算法对采集到的信号进行10层分解,比较本征模函数(IMF)分量相对于原始信号的贡献率及其频域特性,建立了颗粒相含量与各个IMF分量之间的线性关系,并对该线性关系进行实验验证。结果表明:在给料量在4~20 g/s范围内,IMF1、IMF2和IMF3都能很好反映原始信号的某些频率内的特性,可以用来建立颗粒相含量与声发射信号之间的关系;其拟合函数误差均小于10%,平均误差小于5%,与小波包分析法进行对比,EEMD方法得到的结果更为精确。采集到的信号经EEMD分解后的3个分量,均可用以监测气固两相流中的颗粒相含量。
[Abstract]:In order to realize the on-line measurement of particle phase content of gas-solid two-phase flow in pipeline, the acoustic emission signals of gas-solid two-phase flow with different contents are collected by the sensor mounted on the network structure of pipeline section. By means of empirical mode decomposition (EMD) algorithm, the collected signal is decomposed into 10 layers. The contribution rate and frequency domain characteristics of the intrinsic mode function (IMF) component relative to the original signal are compared, and the linear relationship between the particle phase content and each IMF component is established. The experimental results show that both IMF1IMF2 and IMF3 can well reflect the characteristics of the original signal in the range of 4g / s, and can be used to establish the relationship between the particle phase content and the acoustic emission signal. The error of fitting function is less than 10 and the average error is less than 5. Compared with the wavelet packet analysis method, the results obtained by the method are more accurate. The three components of the collected signal are decomposed by EEMD. It can be used to monitor particle phase content in gas-solid two-phase flow.
【作者单位】：华北电力大学国家火力发电工程技术研究中心;
【基金】：中央高校基本科研业务费专项资金资助项目(2015XS83,2017ZZD001)~~
【分类号】：TK124;TM621.2

【相似文献】