COMBINED CLONAL NEGATIVE SELECTION ALGORITHM FOR DIAGNOSTICS OF COMBUSTION IN INDIVIDUAL PC BURNER
Andrzej Smolarz
a.smolarz@pollub.plLublin 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)
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 burnerReferences
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Authors
Andrzej Smolarza.smolarz@pollub.pl
Lublin University of Technology, Institute of Electronics and Information Technologies Poland
Authors
Volodymyr LytvynenkoKherson National Technical University. Department of Informatics & Computer Sciences Ukraine
Authors
Olga KozhukhovskayaCherkasy State Technological University, Department of Computer Systems Ukraine
Authors
Konrad GromaszekLublin University of Technology, Institute of Electronics and Information Technologies Poland
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