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


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

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Published : 2013-12-27


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

Andrzej Smolarz  a.smolarz@pollub.pl
Lublin University of Technology, Institute of Electronics and Information Technologies  Poland
Volodymyr Lytvynenko 
Kherson National Technical University. Department of Informatics & Computer Sciences  Ukraine
Olga Kozhukhovskaya 
Cherkasy State Technological University, Department of Computer Systems  Ukraine
Konrad Gromaszek 
Lublin University of Technology, Institute of Electronics and Information Technologies  Poland