Title: The using of deep neural networks and natural mechanisms of acoustic wave propagation for extinguishing flames

Authors: Jacek Wilk-Jakubowski; Paweł Stawczyk; Stefan Ivanov; Stanko Stankov

Addresses: Department of Information Systems, Kielce University of Technology, 7 Tysiąclecia Państwa Polskiego. Ave., 25-314 Kielce, Poland ' Department of Industrial Electrical Engineering, Kielce University of Technology, 7 Tysiąclecia Państwa Polskiego. Ave., 25-314 Kielce, Poland ' Department of Automation, Information and Control Systems, Technical University of Gabrovo, 4, H. Dimitar, Gabrovo, 5300, Bulgaria ' Department of Automation, Information and Control Systems, Technical University of Gabrovo, 4, H. Dimitar, Gabrovo, 5300, Bulgaria

Abstract: The article presents an innovative method of flame extinguishing with a high-power acoustic extinguisher, which is equipped with a deep neural network (DNN) flame detection module. Experimental results of flame detection with the use of the DNN networks are presented, and then their extinguishing with the use of sinusoidal waves modulated by triangular waveform, as well as with triangular waves without modulation. The article provides a justification for the approach taken, as well as information on the parameters of the signals used and hardware components. The results are discussed taking into account the power supplied to the loudspeaker and the influence of sound pressure on flame extinguishing as a function of a distance from the extinguisher output. The article concludes with a short summary, in which the benefits and potential application of the technology were indicated.

Keywords: acoustic extinguisher; acoustic testing; acoustic waves fire suppression; amplitude modulation; deep neural networks; DNN; extinguishing effect; fire detection; firefighting; fire retardation; non-invasive extinguishing of the flames; TensorFlow; wave modulation.

DOI: 10.1504/IJCVR.2022.121166

International Journal of Computational Vision and Robotics, 2022 Vol.12 No.2, pp.101 - 119

Received: 13 Oct 2020
Accepted: 21 Nov 2020

Published online: 24 Jan 2022 *

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