For the NOx concentration at the inlet of denitration reactor for coal-fired boiler, an important parameter in the combustion process for the boiler, the precision of conventional NOx analyzer is low. Therefore, a NOx emission prediction model for the boiler was established based on the support vector regression (SVR) algorithm, with mean square error (MSE) as the evaluation function for the model. The genetic algorithm (GA) was adopted to optimize relevant parameters of the model, and the NOx emission was predicted through programming. A simulation verification was carried out based on the field data of a 300MW coal-fired unit, and the results showed that the model established by GA-SVR was more effective than SVR and BPNN in the NOx emission prediction.
孙悦, 王雪晶, 于攀, 曹玉波.
基于SVR-GA的燃煤锅炉NOx含量软测量研究
[J]. 吉林化工学院学报, 2021, 38(9): 31-35.
SUN Yue, WANG Xuejing, YU Pan, CAO Yubo.
A Study on the Soft Sensor for NOx Content of Coal-fired Boiler Based on SVR-GA
. Journal of Jilin Institute of Chemical Technology, 2021, 38(9): 31-35.