Study On The Sludge Gasification Syngas Generation Characteristics And BP Neural Network Prediction Model

Developing new, green, environment-friendly and resource utilization sewage sludge treatment technology is not only a requirement of the national economy development, but also the trend of historical development. The organic matter content and heating value of the urban sewage sludge in our country is increasing gradually, which means that it has the potential of energy treatment such as thermal chemical conversion. The dissertation studied the generation characteristics as well as the prediction models of sludge water vapor and water vapor/air mixing gasification syngas; based on the comprehensive analysis of the high output, low pollution sludge gasification process characteristics, valuable theoretical guidance can be provided for the industrial design and operation of sewage sludge energy exploitation equipment. The main work and conclusions are as follows:(1) The influence of temperature, water vapor quality and the sludge content ratio(S/C ratio) on the gasification syngas generation characteristics and sewage sludge energy conversion efficiency were mainly analyzed through gasification experimental study of sludge steam. The results showed that temperature influenced the feature of gasification syngas greatly, and improving temperature not only promoted the generation of high quality synthetic gas but also increased the sludge energy conversion efficiency. When temperature raised from 650℃ to 1050℃, the contents of H2 and CO in the syngas increased by 12.1% and 6.2% respectively, the contents of CO2 and CH4 decreased by 4.8% and 3.2% respectively, and the contents of Sludge gasification cold gas efficiency ηl, carbon conversion efficiency ηc and organic phase conversion efficiency ηv increased by nearly 40%, 18% and 40% respectively; based on the comprehensive consideration of both the energy consumption and gas generation efficiency in the gasification process, the optimal temperature for the H2 rich syngas generation by sludge gasification was around 850℃; the influence of the ratio of S/C on the syngas generation characteristics was twofold, in other words, a too high or low value of S/C ratio would decrease the syngas quality and energy conversion efficiency; when the S/C ratio was 4.74, optimal values could be got for the generation ratio of syngas, calorific value, hydrogen content as well as its yield and the gasification cold gas efficiency ηl.(2) Based on the advantages of both sludge air gasification and steam gasification process, experimental study was adopted to analyze the gasification generation characteristics of air/water vapor mixed sludge syngas. The results showed that compared with the steam gasification, the best value of the H2 yield, CO + H2 yield, synthetic gas calorific value and cold gas efficiency ηl of the mixed gas were 0.38 m3/kg, 0.46 m3/kg, 6.24 MJ/m3 and 59% respectively under different temperatures, which were lower than those of the steam gasification, while the energy consumption of the former was lower than the latter by nearly 5 MJ/kg; compared with pyrolysis, quality of the mixed gasification syngas remained higher, and H2 yield, synthetic gas calorific value and cold gas efficiency ηl were significantly higher than those of pyrolysis gas at the same temperature. In addition, the ratio of gasification medium and sludge sample(Agent/SS) as well as the quality ratio of H2O/O2 should be strictly controlled.(3) The process of sludge gasification was a thermal chemical reaction process which included free radicals reaction, oxygen containing functional groups decomposition reaction, fat side chain rupture, cracking reaction and dehydrogenation reaction, hydrogenation reaction, condensation reaction; with the increment of gasification temperature, chemical structures on the sludge residue surface changed dramatically, O-H and N-H keys,-CH2 and-CH3 groups, C=O groups and C-O and C-Har key gradually disappeared, while the other groups or key structures have been largely decomposed at 650℃ in the same sludge.(4) The BP neural network model of sludge of high temperature steam gasification and steam-air gasification characteristics was established. The prediction accuracy of sludge steam gasification model was relatively high and the relative error lower than 9%; the prediction accuracy of mixed gasification prediction model was lower, which could be improved by methods such as increasing samples and optimizing network.