基于谐波小波分解的静电传感器颗粒流动参数测量  

Measurement of solids flow parameter using electrostatic sensor based on harmonic wavelet decomposition

作　　者：王奇 张文彪[1] 闫勇[1] 王超 

机构地区：[1]华北电力大学控制与计算机工程学院 [2]天津大学电气与自动化工程学院

出　　处：《电子测量与仪器学报》2018年第1期26-32,共7页Journal of Electronic Measurement and Instrumentation

基　　金：国家自然科学基金(61403138,61673291);北京市自然科学基金(3162031)资助项目

摘　　要：为了对气力输送管道进行实时监控,需要对气力输送管道中颗粒流动参数进行测量。然而现有的互相关与空间滤波法大多只能获得颗粒的平均流速,如何从静电信号中提取截面流速分布等信息需要进一步研究。采用一种基于谐波小波分解的方法对环形静电传感器所得静电信号进行研究,实现了传感器横截面不同位置处颗粒流动参数的测量。为了分析环形静电传感器的频率特性,采用带式静电感应实验装置进行了实验研究,分析了静电信号的带宽与橡胶带线速度和径向位置的关系。基于不同位置处静电信号频率特性的差别,对上下游环形电极所得静电信号进行谐波小波分解,并对分解后的上下游信号进行互相关运算,获得了靠近管壁处橡胶带的速度。通过与实际管壁处橡胶带速度的对比,验证了该方法的可行性。In order to monitor the pneumatic conveying process in real time,the solids flow parameters in the pneumatic conveying pipeline should be measured. However,mostly average solids velocity is obtained using cross-correlation method and spatial filtering method. Further research on the extraction of cross sectional velocity profile from the electrostatic signals is needed. In this paper,a method based on harmonic wavelet transform is applied to research the electrostatic signals from a ring-shaped electrostatic sensor. The solids flow parameters at different positions of the cross section of the pipelines are measured. The experiments are conducted on a belttype electrostatic induction test rig to study the frequency characteristics of a ring-shaped electrostatic sensor. The relationships between the bandwidth of the electrostatic signal and the velocity and the position of the belt are analyzed. Based on the difference of the frequency characteristics between different positions,the harmonic wavelet decomposition is applied to the electrostatic signals from the corresponding upstream and downstream sensors and the signals after the decomposition are cross correlated to determine the belt velocity near the pipe wall. In addition,the feasibility of the method is verified by comparing with the actual belt velocity near the pipe wall.

关 键 词：静电传感器 谐波小波变换 频率特性 颗粒流动参数 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]