Radiation measurement based on spectral emissions in industrial flames. (June 2016)

• Record Type: Journal Article
• Authors: Garces, Hugo O.; Arias, Luis; Rojas, Alejandro J.; Carrasco, Claudia; Fuentes, Andres; Farias, Oscar
• Is Part Of: Measurement. Volume 87(2016:Jun.)
• Page Start: 62
• Page End: 73
• Publication Date: 2016-06
• Subjects: Baseline estimation -- Combustion -- Diagnostics -- Flame spectra -- Neural networks -- PCA; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2016.02.066
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: Combustion diagnostics were performed using the total flame radiation. The baseline estimation was implemented based on flame spectral emissions. The method was tested and improved in a bench scale burner. A validation in two common industrial systems was carried out. Uncertainties and time are small and suitable in combustion process optimization. Abstract: A novel combustion diagnostics system based on flame radiation measurement and spectral emissions analysis is presented. The key aspect of this study is the proper estimation of the continuous component or baseline of spectral signals containing spurious discontinuities. We compare both, a PCA based method against an alternative method based on an Artificial Neural Networks model. The accuracy and computational cost for baseline estimation in practical industrial applications is analyzed, in order to incorpore the radiation measurement as a variable suitable for control decisions. Several experiments in industrial facilities demonstrate the suitability of radiation measurement via flame spectrum analysis, in particular the relation between the proposed optical variable and the process operational conditions in the case of an oil boiler for steam production and a ladle furnace preheating process. As results, the methodology based on principal components analysis (PCA) provides high accuracy for baseline estimation in flame spectra, with metrics of RMSE ≈ 0.1 · 10 - 4 and GFC > 0.99 with fast computation times, smaller than typical flame flickering.