COMBINED CLONAL NEGATIVE SELECTION ALGORITHM FOR DIAGNOSTICS OF COMBUSTION IN INDIVIDUAL PC BURNER
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.
Artificial Immune Systems; industrial diagnostics; pulverised coal burner
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