改性酚醛泡沫脱除SO2/NOx影响因素模型

改性酚醛泡沫具有良好的吸附性能，可用于脱除气态污染物，需深入研究其脱除效率与各影响因素间关系。首次引入支持向量机建立改性酚醛泡沫吸附反应床模型，研究在不同温度、气质比、含氧量等影响因素下改性酚醛泡沫脱除二氧化硫、氮氧化物等气态污染物的脱除效果及最优反应条件。烟气模拟脱硫脱硝实验确定RBF-ε-SVM模型为反应器内最优污染物浓度分布预测模型，惩罚系数c=100，gamma因子g=0.1。基于最优模型的各影响因素实验表明：氧气含量在6%时改性酚醛泡沫脱硫脱硝效果最佳；随着质气比的增加脱除效果增强；反应温度在80 ℃内脱除SO2和NO的效率随着烟气温度的升高而降低。该模型可用于改性酚醛泡沫吸附反应床的最优工况选择，反应器内浓度分布的在线监控，以及指导反应器的放大、中试。

Influencing factors of SO2/NOx removal by activated carbon modified phenolic foam

A modified phenolic foam with excellent properties was used in this research to remove gaseous pollutants. The relationships between the removal rate of SO2/NO and several influencing factors of such were studied using a support vector machine (SVM)that simulates the gaseous pollutants removal process by the modified phenolic foam. Processing experimental data on the removal of SO2/NO by the modified phenolic foam with different mass gas ratios,oxygen contents,and temperaments were obtained. Taming the data to determine the RBF-ε-SVM model for optimal predictive models that punishing factor c=100 and gamma factor g=0.1. The RBF-ε-SVM model predicted the distribution of SO2/NO concentration in the reactor. The predicting concentration was visualized through MATLAB software. The results showed that 6% oxygen in the flue was the most advantageous for removing SO2/NO and a higher mass gas ratio was favorable for SO2/NO removal. The removal efficiency of SO2 and NO decreased as the gas temperature increased below 80℃. The model can be used to select the optimal operating conditions for the modified phenolic foam adsorption reaction bed,reactor concentration distribution prediction,and guidance for reactor scale-up.