COMBINED CLONAL NEGATIVE SELECTION ALGORITHM FOR DIAGNOSTICS OF COMBUSTION IN INDIVIDUAL PC BURNER

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DOI

Andrzej Smolarz

a.smolarz@pollub.pl

Volodymyr Lytvynenko

immun56@gmail.com

Olga Kozhukhovskaya

olga-kozhuhovska@mail.ru

Konrad Gromaszek

k.gromaszek@pollub.pl

Abstract

In pulverised coal (PC) burners that are most widespread in Poland an individual air excess ratio rules an amount of pollution generated, yet there is a lack of method that allows measurement of output parameters of a burner. It is therefore necessary to use indirect methods, which could primarily include acoustic, and optical methods. These methods are non-invasive and can provide virtually not delayed and additionally spatially selective information about the combustion process. Additional problems are generated biomass co-firing. The article shows application of relatively new class of classification methods – the artificial immunology algorithms to the combustion process diagnostics consisting in detection of incorrect air excess in PC burner.

Keywords:

Artificial Immune Systems, industrial diagnostics, pulverised coal burner

References

Article Details

Smolarz, A. ., Lytvynenko, V. ., Kozhukhovskaya, O. ., & Gromaszek, K. (2013). COMBINED CLONAL NEGATIVE SELECTION ALGORITHM FOR DIAGNOSTICS OF COMBUSTION IN INDIVIDUAL PC BURNER. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 3(4), 69–73. https://doi.org/10.35784/iapgos.1484