Self-adaptive CH<sub>4</sub> concentration detection system based on infrared spectrum absorption principle

Wei-lin Ye; Xin Yu; Chuan-tao Zheng; Cong-xin Zhao; Menglong Cong; Zhan-wei Song; Yi-ding Wang

doi:10.1007/s11801-011-0166-0

Optoelectronics Letters ›› 2011, Vol. 7 ›› Issue (3) : 217-221. DOI: 10.1007/s11801-011-0166-0

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Self-adaptive CH₄ concentration detection system based on infrared spectrum absorption principle

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Abstract

Considering that the noises resulting from low modulation frequency are serious and cannot be totally eliminated by the classic filters, a novel infrared (IR) gas concentration detection system based on the least square fast transverse filtering (LS-FTF) self-adaptive modern filter structure is proposed. The principle, procedure and simulation on the LS-FTF algorithm are described. The system schematic diagram and key techniques are discussed. The procedures for the ARM7 processor, including LS-FTF and main program, are demonstrated. Comparisons between the experimental results of the detection system using the LS-FTF algorithm and those of the system without using this algorithm are performed. By using the LS-FTF algorithm, the maximum detection error is decreased from 14.3% to 5.4%, and also the detection stability increases as the variation range of the relative error becomes much smaller. The proposed LS-FTF self-adaptive denoising method can be of practical value for mid-IR gas detection, especially for weak signal detection.

Keywords

Reference Channel / Minimum Detection Level / ARM7 Processor / Pure Signal / Weak Signal Detection

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Wei-lin Ye, Xin Yu, Chuan-tao Zheng, Cong-xin Zhao, Menglong Cong, Zhan-wei Song, Yi-ding Wang. Self-adaptive CH₄ concentration detection system based on infrared spectrum absorption principle. Optoelectronics Letters, 2011, 7(3): 217‒221 https://doi.org/10.1007/s11801-011-0166-0

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This work has been supported by the National “863” Project of China (Nos. 2007AA06Z112, 2007AA03Z446 and 2009AA03Z442), the National Natural Science Foundation of China (No.61077074), and the Science and Technology Department of Jilin Province of China (Nos. 20070709 and 20090422).