Naslov (srp)

Klasifikacija motora automobila sa unutrašnjim sagorevanjem prema pogonskom gorivu na osnovu generisanog zvuka

Autor

Milivojčević, Marko, 1986-

Doprinosi

Ćirić, Dejan G., 1967-
Perić, Zoran, 1964-
Nikolić, Jelena, 1978-
Ćertić, Jelena D., 1970-
Dinčić, Milan, 1983-

Opis (srp)

Noise pollution and exhaust emissions represent significantenvironmental challenges, with vehicle classification based on the type offuel contributing to the reduction of air pollution and improvement of urbanspace management. This research develops an original system for acquiringengine sounds of passenger vehicles under real-world conditions, enablingautonomous vehicle detection, minimal environmental impact, andcompatibility with future IoT systems. Key challenges included optimizingthe microphone position to avoid obstructing vehicle passage, as well asselecting the engine operating mode that carries the most relevant acousticinformation. The system was tested on 350 vehicles, forming a database of475 sound samples, along with the implementation of a method forautomatic extraction of acoustically relevant operating modes.Two groups of audio features suitable for distinguishing fuel typeswere identified: spectrogram representations (mel-spectrograms,gammatonegrams) and psychoacoustic characteristics (loudness, roughness,sharpness, crest factor). Classification was carried out using deep learningmethods (CNN) and unsupervised learning (SOM), with CNN achieving an F1score of up to 97%, and SOM reaching 96.7% after eliminating technicallyfaulty vehicles.The contribution of this research lies in the development of aninnovative acquisition system, the identification of key acoustic features,and the demonstration of machine and deep learning applications in enginesound analysis. The created sound sample database represents a valuableresource for the scientific community and future research in noise analysis,fuel type recognition, and fault detection. The results confirmed that it ispossible to successfully classify vehicles based on fuel type using sound,opening opportunities for traffic monitoring, noise reduction, and thedevelopment of standards for assessing engine sound quality.

Opis (srp)

Biografija autora: list. 137Bibliografija: list. 124-136 Datum odbrane: 7.8.2025. Acoustics

Jezik

srpski

Datum

2025

Licenca

Ovo delo je licencirano pod uslovima licence
Creative Commons CC BY-NC-ND 3.0 AT - Creative Commons Autorstvo - Nekomercijalno - Bez prerada 3.0 Austria License.

http://creativecommons.org/licenses/by-nc-nd/3.0/at/legalcode