基于双通道中红外传感器的气溶胶粒子和气体分析方法

Soocheol Kim, Soyoung Park, Kangbok Lee
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引用次数: 1

摘要

尽管研究人员正在积极研究提高火灾探测器性能的方法,但很少有研究调查探测火灾类型的火灾探测器。火灾类型探测在迅速扑灭火灾和防止火势蔓延方面起着关键作用。我们提出了一种基于非色散红外(NDIR)的双通道中红外(mid-IR)方法,可以检测和分类气溶胶颗粒和气体。采用4.2 μm和4.7 μm中红外发光二极管(led)光源,对CO2和CO具有较强的吸收能力。中红外led分别以900 Hz和1000 Hz调制,以提高信噪比,减少光源之间的干扰。调制光通过透镜和样品,并由光电探测器获得。通过测量4.2 μm和4.7 μm光的透过率来检测气溶胶粒子和气体,并根据测量到的透过率和透过率之比对气溶胶粒子和气体进行分层聚类分类。通过测量透光率来检测各种气溶胶粒子和气体,通过计算簇之间的距离来对气溶胶粒子和气体进行分类。对不同波长波段的光谱透过率进行分析,可以检测到各种气溶胶粒子和气体,进一步提高分类精度。此外,该方法还可以应用于火灾探测,开发一种非常有用的技术,可以对火灾烟雾进行探测和分类,并快速检测火灾类型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Method for Aerosol Particle and Gas Analyses based on Dual-channel Mid-infrared Sensor
Although researchers are actively investigating methods to improve fire detector performance, few studies have investigated fire detectors that detect the type of fire. Fire type detection serves a key role in quickly extinguishing fires and preventing their spread. We present a non-dispersive infrared (NDIR)-based dual-channel mid-infrared (mid-IR) method that can detect and classify aerosol particles and gases. 4.2 μm and 4.7 μm mid-IR light emitting diodes (LEDs) light sources with strong absorption for CO2 and CO are employed. and, and the mid-IR LEDs are modulated with 900 Hz and 1,000 Hz, respectively to increase the signal-to-noise ratio and reduce interference between the light sources. The modulated lights pass through the lenses and sample, and are acquired by a photodetector. The transmittances of the 4.2 μm and 4.7 μm lights are measured to detect the aerosol particles and gases, and the aerosol particles and gases are classified via hierarchical clustering using the measured transmittances and the ratio between the measured transmittances. Various aerosol particles and gases are detected by measuring the transmittance, and the aerosol particles and gases are classified by calculating the distance between clusters. Spectral transmittances analysis of different wavelength bands will enable the detection of various aerosol particles and gases, and further improve the classification accuracy. Furthermore, this method can be applied to fire detection to develop a highly useful technique that can detect and classify fire smoke and rapidly detect the type of fire.
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