Research On Mining And Monitoring Of Characteristic Parameters Of Gas-Solid Two-Phase Flow For Pneumatic Conveying

Pneumatic conveying,also known as air conveying,is a method of transporting solid particles using the energy of the gas phase in a closed pipeline,which has the advantages of cleanliness and flexibility.However,due to the complexity of the coupling of gas-solid two-phase flow in the pipeline,it is difficult to reflect the parameter characteristics inside the pipeline in real time,becoming the main bottleneck for efficient intelligent control systems and affecting the overall degree of intelligence.Therefore,it is necessary to explore effective means for real-time monitoring by mining the characteristic parameters of the gas-solid two-phase flow during pneumatic conveying.Firstly,the CFD-DEM model is used to solve the gas-solid coupling state inside a rectangular cross-section pipeline.In the suspension flow,the main forces acting on particles "sinking and floating" are gravity and Magnus lift.When the difference between the particle velocity and the gas velocity is large,Magnus lift dominates the particle "sinking and floating",while when the difference is small,the particle "sinking and floating" is the result of multiple forces acting together.With the increase of superficial gas velocity and the decrease of solid phase flow rate,the flow pattern gradually changes from a packed flow to a stratified flow with no suspension,a stratified flow with suspension,and a suspended flow.The Venturi tube leads to different characteristics of the suspended stratified flow at low superficial gas velocity and low solid phase flow rate,that is,particles present an upward state at the Venturi narrow passage,while no pure gas phase is observed in the upper pipeline.Secondly,data mining analysis was conducted on the collected images,pressure,superficial gas velocity,and other parameters in the experiment.The study showed that the suspension flow pattern had good uniformity and was suitable for fine control of pneumatic conveying fields.The probability density function and PSD plot of pressure fluctuation signal had good flow pattern recognition features.In the PSD plot,the lower energy can be used as the identification feature of packed flow,the higher lowfrequency part can be used as the significant identification feature of stratified flow,while the higher high-frequency part and the complex low-frequency part can be used as the significant identification feature of suspended flow.For the suspended flow,the curve of and is a first-order relationship,and the spacing between different curves is a first-order relationship with the mass flow rate of solid phase.Therefore,the solid phase mass flow rate can be calculated from the pressure signal alone with the help of this law.Then,efficient methods for removing accumulated materials in the pneumatic conveying system were explored due to the interference factors of particle accumulation and external airflow in the monitoring process of solid phase flow rate.The study showed that a large amount of particle accumulation would occur in the sampling tube,which would affect the accuracy of pressure signal acquisition.Therefore,this study chose to place the sampling tube above the conveying tube to minimize particle accumulation.Meanwhile,considering the efficiency of external airflow removal and the structure of the sampling tube,a ventilation pipe structure of-30° was selected.However,external airflow would cause the measurement results of pressure to be biased towards high values.To solve this problem,this study chose to introduce external airflow with high frequency and short duration,and avoided the accuracy drop caused by the instantaneous introduction of external airflow through the control system adjustment.Finally,for the industrial site flow pattern,solid-phase flow real-time monitoring and historical data storage and query needs.The solid phase flow calculation component and historical data storage and query component are built with the open source Rising Wave flow database as the core,supplemented by the external airflow control component,front-end page component,and pressure signal acquisition component to build a real-time monitoring software system for pneumatic conveying parameters.And the accuracy experiments are conducted in industrial sites.In the uniform flow real-time monitoring site,the accuracy is higher in the selected 1s window time,94.37%-99.04%.And in the uneven flow cumulative monitoring sites,the accuracy is 98.93%-99.93%.And the software is more stable and scalable.The thesis has 47 figures,21 tables and 101 references.