| Summary: | Researchers analyzed high resolution operational data from three recovery boilers using the princi - pal component analysis (PCA) feature of a multivariate statistical analysis program to identify major operating varia - bles that contributed to fouling and plugging. The results show that PCA can be used to visualize the variability relat - ed to long-term fouling trends in the boilers and to graphically distinguish changes in the boiler fouling condition caused by operational variability over a short period. This represents a major step forward in identifying operating variables that might be adjusted to minimize fouling, and in developing an on-line fouling monitoring technology based on PCA. This work was conducted as part of the research program on “Increasing energy and chemical recovery efficiency in the kraft process,” jointly supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and a con - sortium of the following companies: AbitibiBowater, Alstom Power, Andritz, Aracruz Celulose, Babcock & Wilcox, Boise Paper Solutions, Carter Holt Harvey, Celulose Nipo-Brasileira, Clyde-Bergemann, Diamond Power International, Domtar, DMI Peace River Pulp, Georgia Pacific, International Paper, Irving Pulp & Paper, Metso Power, MeadWestvaco, Stora Enso Research, Tembec, and Votorantim Celulose e Papel.
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