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基于激光的深度神经网络选择性 BTEX 传感。

Laser-based selective BTEX sensing using deep neural networks.

出版信息

Opt Lett. 2022 Jul 1;47(13):3247-3250. doi: 10.1364/OL.459719.

Abstract

A mid-infrared absorption-based laser sensor is developed for selective and simultaneous benzene, toluene, ethylbenzene, and xylenes (BTEX) measurements under ambient conditions. The sensor is based on a distributed feedback inter-band cascade laser emitting near 3.3 µm. Wavelength tuning and deep neural networks were employed to differentiate the broadband absorbance of BTEX species. The sensor was validated with gas mixtures and real-time measurements were demonstrated at a temporal resolution of 1 s. Minimum detection limits for BTEX in air are 8, 20, 5, and 46 ppm, respectively. This sensor can be utilized to monitor BTEX emissions in the petrochemical, rubber, and paint industries to avoid hazardous health effects.

摘要

研制了一种基于中红外吸收的激光传感器,用于在环境条件下选择性和同时测量苯、甲苯、乙苯和二甲苯(BTEX)。该传感器基于发射近 3.3 µm 的分布式反馈带间级联激光。采用波长调谐和深度神经网络来区分 BTEX 物种的宽带吸收。该传感器通过混合气体进行了验证,并以 1 s 的时间分辨率进行了实时测量。空气中 BTEX 的最低检测限分别为 8、20、5 和 46 ppm。该传感器可用于监测石化、橡胶和油漆行业的 BTEX 排放,以避免对健康造成危害。

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