Research On Gas-solid Two-phase Flow Measurement Based On The Decomposition Of Electrostatic Induced And Transferred Signals

The online measurement of the gas-solid two-phase flow parameters is of great significance for energy saving and emission reduction,improving production efficiency and ensuring the safe operation of the system.Electrostatic sensor has the advantages of simple structure,good wear resistance and pressure resistance,which has been widely used in the field of gas-solid two-phase flow parameter detection.At present,the research of gas-solid two-phase flow detection by electrostatic method is carried out along the two routes of “electrostatic induction” and “contact charge transfer”.Aiming at the comprehensive utilization of the two mechanisms,this paper focuses on the decomposition of electrostatic induced and transferred signals,the characterization of flow state and the reconstruction of velocity distribution by the induced signal,and the characterization of particle mass flow rate of gas-solid two-phase flow by the combination of transferred and induced current signals.The main research work and results are as follows.1.By using the different waveform characteristics of induced and transferred current signals in time domain,the signal waveform similarity is used as the quantitative basis for the selection of front-end amplifier circuit parameters,an algorithm for extracting the induced signal and the transferred signal based on the time domain waveform characteristics is proposed.The ensemble empirical mode decomposition(EEMD)is selected to decompose the coupling signal.By analyzing the effect of the correlation coefficient of the upstream and downstream component signal and the correlation coefficient of the autocorrelation function of the upstream and downstream component signal,it is found that the correlation coefficient of the autocorrelation function has higher reliability.Finally,taking the correlation coefficient of the autocorrelation function as the index,the corresponding intrinsic mode function(IMF)is extracted to reconstruct the induced signal.For the residual component signal,the slope of the integral curve is calculated to obtain the transferred current signal,which realizes the effective extraction of the induced current signal and the transferred current signal.The experimental results show that this method has higher accuracy and stability than the direct correlation method.The mean absolute percentage error is reduced from 4.81% to1.30%,and the average relative standard deviation is reduced from 5.71% to 1.01%.The experimental results of gas-solid two-phase flow velocity measurement show that compared with other methods,the average relative standard deviation of this method(2.46%)is higher than that of direct cross-correlation method(2.87%)and discrete wavelet transform method(2.69%).2.In view of the problem that it is impossible to obtain the minimum pressure drop velocity by the phase diagram under the condition of low particle mass flow rate,a method to determine the minimum pressure drop velocity based on four arc electrode electrostatic sensor is proposed.In order to reflect the particle state of gas-solid twophase flow near the electrode,an electrostatic sensor with four arc electrodes is designed,and the particle random motion energy ratio(PRMER)is defined by using empirical mode decomposition(EMD)and Hurst index analysis method.By comparing and analyzing the the difference of PRMERs of particles measured on different electrodes in the section,the minimum pressure drop velocity can be determined under the condition of low particle mass flow.3.Due to the non-uniform particle distribution,the Electrostatic Direct Velocity Tomography(EDVT)is no longer applicable.In this paper,the Electrostatic Charge Distribution-based Direct Velocity Tomography(ECDDVT)method for gas-solid twophase flow is proposed.The correlation sensitivity is modified by introducing the actual charge distribution,and the velocity distribution measurement of charged particles is realized by combining the correlation velocity between the upstream and downstream electrodes.In view of the problem that the existing detection technology can not provide real-time and actual reference for the solid velocity distribution,a set of simulation evaluation platform combining gas-solid flow field with electrostatic field is constructed.The average particle velocity is obtained by assigning weight coefficients to the grid cells according to the relative charge and combining with the velocity distribution.In the simulation results,the image correlation coefficient of the ECDDVT method is higher than that of the EDVT method,and the average image correlation coefficient is increased from 0.5681 to 0.7760,and the absolute percentage error of the average particle velocity is reduced from 18.3% to 3.7%.In the experiments of the belt type electrostatic velocity measurement facility and the gas-solid two-phase flow rig,the ECDDVT is better than EDVT in the particle velocity measurement accuracy and reflecting the velocity at the center of the pipe.4.Aiming at the problem that the signal processing method and relationship are not unified in the particle mass flow rate characterization model,the characterization model by combining the transferred and induced current signal is established.Based on the study of the relationship between transferred current signal and the charge state of particle flow,combined with the state of charge obtained from induced current signal,a unified characterization of particle mass flow rate of gas-solid two-phase flow by the combination of transferred and induced current signals.Under the conditions of particle mass flow rate of 0.022-0.045 kg/s and superficial gas velocity of 10.41-23.05 m/s,compared with the model using transferrd and induced current signals alone,the mean absolute percentage error of the particle mass flow rate measured by the proposed method is reduced from 8.27% and 16.07% to 6.92%.