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- W2467687873 abstract "The authors have performed a series of tests examining the use of optical flame emissions to provide continuous information on burner performance. These tests are part of the program to investigate advanced combustion control strategies. They used a bench-scale combustion system fired with fuel oil and operated over a wide range of conditions. A conventional CCD-array camera collected unfiltered flame images from which analysis routines extracted potentially important parameters. An artificial neural network was trained to relate image parameters to conventional combustion performance measures. They then evaluated the ability of the trained network to predict combustor emissions using only flame image data. They focused on two measures of combustor performance--carbon monoxide and nitrogen oxide concentrations in the flue gas. A conventional continuous emission monitoring system measured exhaust gas composition. They gathered data at conditions representing fouled, normal, lean, and high temperature operation. Carbon monoxide emissions correlated moderately with the image parameters selected. The trained network was very accurate at predicting nitrogen oxide emissions." @default.
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- W2467687873 date "1998-12-31" @default.
- W2467687873 modified "2023-09-23" @default.
- W2467687873 title "Prediction of emissions from liquid combustion systems" @default.
- W2467687873 hasPublicationYear "1998" @default.
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