Paper
20 February 2006 Study on infrared carbon monoxide monitoring system used in mine
Yukai He, Rulin Wang, Zhongqi Liu, Shufang Wang, Junmin Deng, Zhonghui Guan
Author Affiliations +
Proceedings Volume 6041, ICMIT 2005: Information Systems and Signal Processing; 604122 (2006) https://doi.org/10.1117/12.664357
Event: ICMIT 2005: Merchatronics, MEMS, and Smart Materials, 2005, Chongqing, China
Abstract
Carbon monoxide does enormously harm to people and safety production in coal mine and other industries. But because the situation in coal mine is complicated and the interference factors are diversified, at present carbon monoxide detection system has the general problems of low detecting precision, easily poisoning and aging, short service life, narrow measurement range and bed anti-jamming ability. Carbon monoxide concentration is detected by using the infrared absorption principle, and this detection is applied in many fields. A new optics structure was developed with a reference gas cell, dual light sources and dual detectors in this paper, it could compensate to power source anti-jamming, mismatch of the detectors, gas cell material's absorption, and dust's influence. In addition, an infrared carbon monoxide sensor's mathematical model was built by adopting radial basic function's (RBF) neural network model, so as to dispel the influence of temperature, pressure and humidity. A momentum factor's gradient descending method could be applied to adjust the parameters of RBF neural network. The experimental results show that whole system runs very well with a high precision, a strong capacity of anti-jamming, a wide measurement range, a good selectivity, and an online detecting ability.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yukai He, Rulin Wang, Zhongqi Liu, Shufang Wang, Junmin Deng, and Zhonghui Guan "Study on infrared carbon monoxide monitoring system used in mine", Proc. SPIE 6041, ICMIT 2005: Information Systems and Signal Processing, 604122 (20 February 2006); https://doi.org/10.1117/12.664357
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Cited by 6 scholarly publications.
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KEYWORDS
Carbon monoxide

Sensors

Infrared sensors

Infrared radiation

Absorption

Neural networks

Infrared detectors

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