Mathematical method analyzing the accuracy of velocity measurement based on cross-correlation

2010 ◽  
Author(s):  
Chen Min ◽  
Xu Xuelin
Keyword(s):  
Mathematical Method ◽  
Velocity Measurement ◽  
Cross Correlation

Study on Velocity Measurement of Gas/Solid Flow Based on Electrostatic Sensor

2014 ◽  
Vol 614 ◽  
pp. 275-278
Author(s):  
Yu Tang ◽  
Xiang Deng ◽  
Shuo Tian
Keyword(s):  
Measurement System ◽  
Velocity Measurement ◽  
Flow Measurement ◽  
Cross Correlation ◽  
Low Cost ◽  
High Sensitivity ◽  
Two Phase ◽  
Solid Flow ◽  
Correlation Algorithm ◽  
Electrostatic Induction

Electrostatic sensor is based on the principle of electrostatic induction. It is widely used for gas/solid two-phase flow measurement because it has the advantages of simple structure, high sensitivity, low cost, etc. In this paper, a velocity measurement system of gas/solid flow based on electrostatic sensor and cross-correlation algorithm is discussed. Electrostatic sensor with circular electrode is adopted. By COMSOL optimum simulation, the axial length of the electrode is designed. The signal conditioning circuits are discussed and cross-correlation algorithm is analyzed. The initial experimental results demonstrate that the velocity measurement system of gas/solid flow designed in this paper is feasible.

A Combined Interpolation Method for Cross Correlation Based Particle Velocity Measurement

2012 ◽  
Vol 508 ◽  
pp. 67-70
Author(s):  
Gang Yang ◽  
Wei Dong Li ◽  
Yu Tao Wang ◽  
Ming Yu Li
Keyword(s):  
Correlation Function ◽  
Velocity Measurement ◽  
Cross Correlation ◽  
Interpolation Method ◽  
Sampling Rate ◽  
Time Delay Estimation ◽  
Parametric Models ◽  
Center Frequency ◽  
Estimation Accuracy ◽  
Particulate Solids

Cross correlation techniques have been proved to be a valuable tool for online continuous velocity measurement of particulate solids in pneumatic pipelines. In order to reduce computational complexity the sampling frequency is usually kept as low as possible, and the peak in the correlation function is found by interpolating the correlation function. Parabola functions are commonly used as parametric models of the cross correlation function in time delay estimation. However, the parabolic-fit interpolation method introduces a bias at low sampling rate to the center frequency ratio of input signal. In this paper, a combined interpolation method is proposed to improve the estimation accuracy. Experiments are carried out to evaluate the performance of the proposed interpolation method for low sampling rate. The experimental results have been promising and have shown the potential of the proposed method for particle flow velocity measurements.

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