Vibroacoustic Real Time Fuel Classification in Diesel Engine

• Autorzy: Bąkowski A. , Kekez M. , Radziszewski L. , Sapietova A.

Identyfikatory

DOI

10.24425/123910

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

fuel recognition; classification trees; particle swarm optimization (PSO); random forest

• Wydawca: Instytut Podstawowych Problemów Techniki PAN ; Komitet Akustyki PAN ; Polskie Towarzystwo Akustyczne
• Czasopismo: Archives of Acoustics
• Rocznik: 2018
• Tom: Vol. 43, No. 3
• Strony: 385--395
• Opis fizyczny: Bibliogr. 31 poz., tab., wykr.

Twórcy

autor

Bąkowski A.

• Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, Al. Tysiąclecia Państwa Polskiego 7, 25-314 Kielce, Poland

autor

Kekez M.

• Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, Al. Tysiąclecia Państwa Polskiego 7, 25-314 Kielce, Poland

autor

Radziszewski L.

• Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, Al. Tysiąclecia Państwa Polskiego 7, 25-314 Kielce, Poland

autor

Sapietova A.

• University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).