Multivariate Image Analysis (MIA) for Industrial Flare Combustion Control

Autor:	David Castiñeira, Thomas F. Edgar, Blake C. Rawlings
Rok vydání:	2012
Předmět:	Multivariate statistics Meteorology General Chemical Engineering Airflow General Chemistry Combustion Industrial and Manufacturing Engineering law.invention law Principal component analysis Range (statistics) Environmental science Projection (set theory) Remote sensing Flare Crosswind
Zdroj:	Industrial & Engineering Chemistry Research. 51:12642-12652
ISSN:	1520-5045 0888-5885
DOI:	10.1021/ie3003039
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::4e026d46f298c5e1db205759ad3424d9 https://doi.org/10.1021/ie3003039 Zobrazit plný text záznamu