On-line fuel identification using digital signal processing and soft-computing techniques

This paper presents a novel approach for on-line fuel identification using digital signal processing and soft-computing techniques. A flame detector containing three photodiodes is used to derive multiple signals covering a wide spectrum of the flame from infrared to ultraviolet through visible band. Advanced digital signal processing and soft-computing techniques are deployed to identify the dynamic ´finger-prints´ of the flame both in the time and frequency domains and ultimately the type of fuel being burnt. A series of experiments was carried out using a 0.5MW_th combustion test facility operated by Innogy plc, UK. The results obtained demonstrate that this approach can be used to identify the type of fuel being burnt under steady combustion conditions.