Research On Mass Flow Rate Measurement Of Gas Solid Two Phase Flow Based On Acoustic Method

Gas-solid two-phase flow is widespread in the power,pharmaceutical,metallurgy,food,and various other industrial processes.Solid mass flow is one of the most important gas-solid two-phase flow,the measurement of particle mass flow is important for the measurement and control of industrial process.Numerous scholars at home and abroad offered different methods to measure the particle mass flow rate.As one of those methods,the acoustic method got the attention of numerical researchers by its advantages.For example,ultrasonic waves have a broad frequency range,leading to Multi-selected scope;ultrasonic penetration is stronger than audible sound,the gas-solid two-phase flow could be measured without secondary treatment;The ultrasonic method is non-contact measurement,which is accessing to movable online measurement;Acoustic emission signal is extremely sensitive to the particle feature parameters,it is more safer than other methods.Meanwhile,the acoustic emission method do not require signal generation,which means less devices than active ultrasonic method.This research focus on the application of the acoustic method in gas-solid mass flow rate measurement.First,the gas-solid mass flow rate was studied by ultrasonic method(active acoustic method).Ultrasonic measurement research is divided into two research directions:1.The particle mass flow rate is predicted by the combination of ultrasonic attenuation coefficient with Monte Carlo algorithm.2.By studying the influence of different gas-solid two-phase flow parameters on ultrasonic sound velocity,the feasibility of ultrasonic sound velocity is researched.After that,the acoustic emission(passive acoustic method)signal generated by particle-to-probe collision during gas-solid two-phase flow operation is studied.the relationship between particle mass flow rate and acoustic emission signals was established.The dissertation centered on the following points and achieved corresponding achievements:Research on the generation mechanism of acoustic emission signals in gas-solid two phase flow.Based on Hertz collision theory,The calculation of main frequency and energy of acoustic emission were derived,introducing the particle distribution function(Rosin-Rammler function)into the calculation of acoustic emission energy,developing a new acoustic emission energy calculation model,which could provide a theoretical basis for the accurate calculation of acoustic emission energy.Based on the signal particle scattering and absorption theory,using the combination of ultrasonic attenuation coefficient and Monte Carlo method to predict the particle mass flow rate,ultrasonic attenuation coefficient-Monte Carlo calculation model was established.The results show that this method could accurately predict the sound pressure distribution on the surface of single particle and the sound attenuation coefficient in the dilute gas-solid two-phase flow.Further research can be achieved to predict the particle volume fraction and calculate the particle mass flow rate.By comparison,it could be concluded that this method can provide a theoretical basis for the effective measurement of the particle mass flow rate in dilute phase gas-solid two-phase flow.Based on the multiple ultrasonic model in gas-solid two-phase flow,the effect of multi-parameters on the different velocity model were analyzed,the measurement of particle mass flow rate can be achieved based on the ultrasonic velocity method.The results show that the changes of the continuous phase sound velocity has the greatest influence on the ultrasonic velocity measurement.From the perspective of continuous phase,the influence of other parameters at the same level,the density's influence is bigger than others.From the perspective of particle phase,the change of the particle phase sound velocity has the minimum influence on the ultrasonic velocity.However,the influence of particle density is the largest than other particle parameters.Comparing the same parameter of two phase,the parameters of continuous phase is larger than particle phase.Therefore,in the process of measurement,more accurate continuous phase parameters are required.In the experimental measurement range,the average error of ultrasonic sound velocity method is 5.92%.The results show that ultrasonic sound velocity can be treated as one of the effective method to measure the particle mass flow rate.An acoustic emission signal acquisition method based on intrusive mesh probe is proposed.The mesh probe is used to circumvent the influence of pipeline parameters on the acoustic emission signal in the traditional adherent measurement method.Meanwhile,EEMD algorithm and MSECF parameter were introduced into acoustic emission signal measurement.the acoustic emission technology was used to realize the measurement of particle mass flow rate.By comparing the four type probes,the relative error of the mesh probe is 1.5%,the acoustic emission signal acquired by the wire mesh probe is better than the T-type probe and adherent probe on plexiglass pipe.For the adherent type probe,the relative error of signal received by plexiglass pipe is 5.8%,while the relative error of stainless steel pipe signal is 0.3%.Comparing with the adherent mesh probe,the wire mesh probe with fixed characteristic parameters avoids the influence of the pipe characteristics on the acoustic emission signal.Then the acoustic emission signal is only affected by the particle parameters.Extracting the effective IMF components by EEMD algorithm,the relationship of IMF components and particle mass flow rate was established under single particle radius condition.This method is more universal and suitable for particle measurement of gas-solid two-phase flow under various pipeline parameters.The maximum error of this method is 7.61%,and the average error is blow 5%,which is lower than the error of wavelet packet analysis method.In the case of multiple particle sizes,introducing MSECF to distinguish the particle sizes,then the particle mass flow rate can be determined by the relationship of IMF components and particle mass flow rete.In addition,the combination of IMF components and BP neural network could be used to measurement the particle mass flow rate.The number of hidden layers and number of neurons were explored.The results show that,the neural network performance parameter achieved optical performance when the input parameter is IMF1 to IMF 4,the number of hidden layers is 2 and the number of neurons is 13.The joint model has an average error of 8.22%,which can be used to measure the particle mass flow rate.The results show that,in the case of the mesh probe and the EEMD algorithm,this BP neural network could achieve the measurement of particle mass flow rate.