N2 - Five models and methodology are discussed in this paper for constructing classifiers capable of recognizing in real time the type of fuel injected into a diesel engine cylinder to accuracy acceptable in practical technical applications. Experimental research was carried out on the dynamic engine test facility. The signal of in-cylinder and in-injection line pressure in an internal combustion engine powered by mineral fuel, biodiesel or blends of these two fuel types was evaluated using the vibro-acoustic method. Computational intelligence methods such as classification trees, particle swarm optimization and random forest were applied. L1 - http://www.journals.pan.pl/Content/108110/PDF/123910.pdf L2 - http://www.journals.pan.pl/Content/108110 PY - 2018 IS - No 3 EP - 395 DO - 10.24425/123910 KW - fuel recognition KW - classification trees KW - particle swarm optimization KW - random forest A1 - Bąkowski, Andrzej A1 - Kekez, Michał A1 - Radziszewski, Leszek A1 - Sapietova, Alžbeta PB - Polish Academy of Sciences, Institute of Fundamental Technological Research, Committee on Acoustics VL - vol. 43 DA - 2018.09.25 T1 - Vibroacoustic Real Time Fuel Classification in Diesel Engine SP - 385 UR - http://www.journals.pan.pl/dlibra/publication/edition/108110 T2 - Archives of Acoustics