Research on Flame Radical Imaging and Extreme Learning Machine to Prediction of NOx Emissions

Authors

Xinli Li, 1.School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China;;
Li Nan, 1.School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China;;
Yujia Sun, 1.School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China;;
Lu Gang, 2.School of Engineering and Digital Arts, University of Kent, Kent CT2 7NT, UK;
Yan Yong, 1.School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China;;2.School of Engineering and Digital Arts, University of Kent, Kent CT2 7NT, UK;
Liu Shi, 1.School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China;;

Abstract

Abstract: Flame radicals are crucial for an in-depth understanding of the combustion mechanisms. The spectral characteristics of flame radicals were studied based on digital imaging and feature extraction techniques. The information obtained was used to establish the extreme learning machine (ELM) model which can be used to predict the NOx emissions based on the experimental data and digital simulation from a biomass-gas-air combustion process. The digital images of four flame radicals, i.e., OH*, CN*, CH* and C₂*, were collected using an EMCCD (Electron Multiplying Charge Coupled Device) camera. The image segmentation was performed using the fuzzy C-means (FCM) algorithm, and image features were extracted. Finally, the ELM model was built for the prediction of NOx emissions based on the radical features and flame temperture. The experimental data on a gas-biomass combustion test rig demonstrate the validity of the proposed ELM model.

Recommended Citation

Li, Xinli; Nan, Li; Sun, Yujia; Gang, Lu; Yong, Yan; and Shi, Liu (2020) "Research on Flame Radical Imaging and Extreme Learning Machine to Prediction of NOx Emissions," Journal of System Simulation: Vol. 28: Iss. 5, Article 24.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss5/24

First Page

1179

Revised Date

2015-11-18

DOI Link

https://doi.org/

Last Page

1185

CLC

TP183

Recommended Citation

Li Xinli, Li Nan, Sun Yujia, Lu Gang, Yan Yong, Liu Shi. Research on Flame Radical Imaging and Extreme Learning Machine to Prediction of NOx Emissions[J]. Journal of System Simulation, 2016, 28(5): 1179-1185.