Research on infrared optical CO detection based on BP neural network algorithm

Xiaodong Wang; Xian Shi; Hu Duan; Laishan Zhou; Hexiang Wu

doi:10.1117/12.3032111

8 June 2024 Research on infrared optical CO detection based on BP neural network algorithm

Xiaodong Wang, Xian Shi, Hu Duan, Laishan Zhou, Hexiang Wu

Proceedings Volume 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024); 131710K (2024) https://doi.org/10.1117/12.3032111
Event: 3rd International Conference on Algorithms, Microchips and Network Applications (AMNA 2024), 2024, Jinan, China

Abstract

The article takes the prevention of accidents caused by CO in daily life as the background and introduces a method of CO concentration detection parameter modulation and system denoising. The system adopts a hybrid detection technology of tunable semiconductor laser absorption spectroscopy (TDLAS) and wavelength modulation (WMS). It is achieving effective suppression of background gases in the environment. The system is combined with a BP neural network to invert the concentration of CO in the gas. Finally, the system noise is processed through wavelet transform to achieve the completion and optimization of the smoke detection algorithm. This has high practical value and guiding significance for the combination of TDLAS CO detection simulation system and hardware system of WOA-BP neural network.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaodong Wang, Xian Shi, Hu Duan, Laishan Zhou, and Hexiang Wu "Research on infrared optical CO detection based on BP neural network algorithm", Proc. SPIE 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024), 131710K (8 June 2024); https://doi.org/10.1117/12.3032111

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