| In the industrial production of thermal power generation,the powder combustion material is blown into the pipeline at a certain speed to form a mixed fluid of gas and powder solid particles.The random directional movement of the fluid in the pipeline is called gas-solid two-phase flow.The size of the fluid mass flow directly affects the thermal power generation efficiency,the degree of environmental pollution and the operating state of the equipment.However,wind speed is a key factor affecting mass flow.Therefore,how to use the fluid parameters to identify and detect the wind speed in the pipeline becomes a key issue.Based on the "Sino-British Joint Laboratory of Particles and Two-Phase Flow" jointly established by North Central University and Teesside University,this paper uses the electrostatic method to study the correlation between wind speed and electrostatic signal.and the result is as follows:1)Theoretical research and simulation analysis of electrostatic sensor.Based on the macro-structural characteristics of the "ring electrostatic sensor",the Maxwell software was used to reconstruct it in three dimensions;the "electrostatic method" was used to analyze the microscopic dynamic physical process of the electrode induced charge,and the whole process of the electrode induced charge was simulated.The surface charge density distribution,field strength vector distribution and electric displacement vector distribution of the ring electrode are obtained.The influencing factors of the electrode induced charge sensitivity are analyzed in many aspects,and the correlation result between the electrode width and the particle space position on its induction sensitivity is obtained.The optimization of ring electrodes provides an important basis.2)Research on electrostatic signal detection technology.Aiming at the weak charge signal output by the annular electrostatic sensor,an electrostatic signal conditioning circuit composed of a pre-charge amplifier circuit,a second-order low-pass filter circuit and a signal amplifier circuit is designed to complete the conversion and effective amplification of the charge signal to the voltage signal.The FPGA processor completes the hardware and software design of the digital signal processing module in a targeted manner.The hardware part includes the power supply circuit,the AD acquisition circuit and the SDRAM storage circuit;the software part includes the function implementation of AD acquisition,the function implementation of ROM storage and the FIFO.The function of storage is realized;the simulation results show that the AD acquisition module can complete the acquisition of signals in different frequency bands by adjusting the sampling rate by itself,and the sampling rate can reach up to 250ksps;the ROM memory module completes the data storage work;the FIFO memory module completes the experiment The core work of 16 bit to 8bit of data.3)Research on the correlation between wind speed and electrostatic signal.For the collected original electrostatic signal,the waveform is displayed by MATLAB software,and the initial characteristic analysis of the electrostatic signal in time domain and frequency domain is done;Variational Mode Decomposition algorithm（Variational Mode Decomposition）and particle swarm optimization algorithm（PSO: The VMD algorithm optimized by Particle swarm optimization filters and optimizes the electrostatic signal,and obtains an effective electrostatic signal after filtering.Vector Machine）parameters,completed the classification,identification and prediction of wind speed based on electrostatic signal features,and established a mathematical model between wind speed and electrostatic signal variance through numerical analysis.The experimental results show that the VMD filtering effect after the optimization of the PSO algorithm is better,and the 6 groups of effective electrostatic signals are also concentrated in the extremely small range of 1～20Hz;the accuracy of the SVM prediction model before and after optimization by the GWO algorithm is obtained.It is 72.2% and 96.7% respectively,which verifies the effectiveness of the GWO algorithm and the accuracy of the model for wind speed identification and prediction;through the verification of the mathematical model,it is concluded that there is a positive correlation between the wind speed and the variance of the electrostatic signal,and the maximum error Only 4.5% verified the accuracy of the mathematical model. |
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