Abstract
A new approach for flare monitoring is proposed so that flare combustion efficiency can be predicted online in industrial plants. Multivariate image analysis (MIA), which is based on principal component analysis (PCA) and projection to latent structures (PLS), has been applied to flare combustion systems in order to predict their resulting combustion efficiencies, as a function of the crosswind velocity, using simulated results, and as a function of steam or air flow rates, using experimental tests of a full-size flare. The results show that a multivariate regression model based on flare color images can be used to predict the flare performance over a range of operating conditions for steam-assisted flares. Therefore, simple two-dimensional color images of industrial flares may be a fast, accurate, and inexpensive approach for online monitoring of these industrial combustion systems. This would allow for developing effective flare control and mitigation strategies.
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