NDLI: A Novel Carbon Monoxide Detection System Based on Infrared Absorption Used in Mine

Content Provider	IEEE Xplore Digital Library
Author	Yu-Kai He Ru-Lin Wang Yu-Qiang Yang
Copyright Year	2006
Description	Author affiliation: Dept. of Public Comput. Teaching & Res., BoHai Univ., Jinzhou (Yu-Kai He)
Abstract	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. Considering the complexity of the circumstance and the diversity of the interference factors in mine, dual light sources and four detectors system is introduced into the new optical structure and most of the interference factors such as power source anti-jamming, mismatch of the detectors, gas cell material's absorption, and dust's influence and etc can be compensated. In addition, an infrared carbon monoxide (CO) sensor's mathematical model is 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 can be applied to adjust the parameters of RBF neural network. The experimental results have shown that the whole system has a high precision, a strong capacity of anti-jamming, a wide measurement range, a good selectivity, and an online detecting ability
Sponsorship	IEEE Syst., Man and Cybernetics Hebei Univ.
Starting Page	645
Ending Page	649
File Size	216729
Page Count	5
File Format	PDF
ISBN	1424400619
DOI	10.1109/ICMLC.2006.258392
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-13
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Infrared detectors Gas detectors Electromagnetic wave absorption Interference Mathematical model Neural networks Aging Light sources Optical computing Optical sensors Infrared absorption Carbon monoxide Optics structure Rbf neural network
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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