Research on multi-parameter joint detection of aircraft cargo fire based on GA-BP

Haibin Wang; Hongjuan Ge; Zhihui Zhang; Zonghao Bu; Chen Qu

doi:10.1117/12.2687396

6 November 2023 Research on multi-parameter joint detection of aircraft cargo fire based on GA-BP

Haibin Wang, Hongjuan Ge, Zhihui Zhang, Zonghao Bu, Chen Qu

Author Affiliations +

Proceedings Volume 12921, Third International Computing Imaging Conference (CITA 2023); 1292107 (2023) https://doi.org/10.1117/12.2687396
Event: Third International Computing Imaging Conference (CITA 2023), 2023, Sydney, Australia

Abstract

Aiming at the problem of high false alarm rate of fire detectors, this paper uses the principle of different scattering signals of different wavelengths of light to particles to detect fire smoke, and proposes to use blue light scattering signal (characterized as surface area concentration), infrared light scattering signal (characterized as volume concentration), and temperature joint detection, combined with genetic algorithm to optimize BP neural network - GA-BP neural network, establish a joint detection model of multiple fire characteristic parameters, and train the fire recognition accuracy of the model through experimental data to realize the fire state of different types of combustibles , water vapor and dust and other non-fire interference particulate matter identification.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Haibin Wang, Hongjuan Ge, Zhihui Zhang, Zonghao Bu, and Chen Qu "Research on multi-parameter joint detection of aircraft cargo fire based on GA-BP", Proc. SPIE 12921, Third International Computing Imaging Conference (CITA 2023), 1292107 (6 November 2023); https://doi.org/10.1117/12.2687396

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