Prediction of pollutant emissions of biomass flames using digital imaging, contourlet transform and Radial Basis Function network techniques
Prediction of pollutant emissions of biomass flames using digital imaging, contourlet transform and Radial Basis Function network techniques
复制标题
利用数字成像、轮廓波变换和径向基函数网络技术预测生物质火焰污染物排放
DOI：
10.1109/i2mtc.2014.6860832
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Li N
中科院分区：
文献类型：
--
作者：
Li N
提出了一种基于火焰自由基成像、Contourlets变换和径向基函数网络的生物质燃烧过程NOx排放预测方法。使用光谱成像系统捕获四种火焰自由基（OH*、CN*、CH* 和C2*）的图像。然后，基于轮廓波系数的最佳M项近似来识别图像的特征。通过径向基函数网络建立了自由基图像特征与NOx排放之间的关系。在生物质燃气燃烧试验台上的试验结果表明了所提出的NOx排放预测技术方法的有效性。
This paper presents a method for the prediction of NOx emissions in a biomass combustion process through the combination of flame radical imaging, contourlets transform, and radial basis function network techniques. The images of four flame radicals (OH*, CN*, CH* and C2*) are captured using a spectroscopic imaging system. The features of the images are then identified based on the best M-term approximation of contourlet coefficients. The relationships between the features of radical images and NOx emissions are finally established through the use of the Radical Basis Function network. The test results obtained on a biomass-gas fired test rig show the effectiveness of the proposed technical approach for the prediction of NOx emissions.