Development Of Experimental Equipment For Microwave Cracking And Removal Of Pyrolysis Gas Tar And Optimization Of Process Parameters

Pyrolysis is an advanced technology for the treatment of organic solid waste.However,when the pyrolysis gas enters the subsequent unit,it is easily to condense and generate a large amount of tar,which may block the pipeline.Therefore,to obtain clean combustible gas,the tar in the pyrolysis gas needs to be removed.The traditional tar removal method not only wastes the heat of the pyrolysis gas,but also produces oily sewage that needs to be disposed.Therefore,directly crack and purify the pyrolysis gas would be a better choice.Microwave-assisted pyrolysis is an emerging biomass tar removal technology.In this thesis,a new microwave pyrolysis gas tar removal device is developed and its optimal process parameters are mainly discussed.In this thesis,the tar in the pyrolysis gas is taken as the research object to remove.First,the size of the microwave resonant cavity can be calculated based on the theory and experimental requirements of microwave technology waveguide.Through the HFSS electromagnetic simulation software,the power and feeder position of the microwave device are determined,and the microwave cracking device is developed.Then,an experimental system is built to obtain the pyrolysis mechanism and influencing factors of the tar cracking rate.A regression model in MATLAB is established under the 60 sets of data from the experiments.The parameters of the multiple linear regression,support vector machine and BP neural network models are set after extensive experimentation to establish the regression model.The BP neural network is selected as the regression model algorithm after comparing the effects of the three regression models.Then parameter optimization for particle swarm optimization and genetic algorithm is carried out,and the improved algorithm is used to optimize the regression model respectively.Comparing the optimization effects of the two algorithms,the optimal cracking efficiency and its corresponding process parameters are obtained.Finally,through the practical experiment,the accuracy of the optimal process parameters is verified.