Cross sensitivity reduction of gas sensors using genetic algorithm neural network

Junhua Liu; Yong Zhang; Yonghuai Zhang; Ming Chen

doi:10.1117/12.417392

13 February 2001 Cross sensitivity reduction of gas sensors using genetic algorithm neural network

Junhua Liu, Yong Zhang, Yonghuai Zhang, Ming Chen

Proceedings Volume 4201, Optical Methods for Industrial Processes; (2001) https://doi.org/10.1117/12.417392
Event: Environmental and Industrial Sensing, 2000, Boston, MA, United States

Abstract

12 Infrared absorption method in analyzing gas components is a traditional spectrum analyzing method of gas. Nevertheless, the distribution of the absorption spectrum of a certain kind of gas intercrosses with another's, which means that the absorption peaks of two kinds of gases are near very close. So, when those kinds of gases aforementioned are mixed together, the spectrum analysis will have the cross sensitivity. In this paper, the genetic neural network algorithm is adopted to recognize the patterns of the mixed gases with three components in the simulation recognition. The genetic algorithm decreases the cross sensitivity of the gas sensor. Especially the staged-sectional method is used to increase the recognition accuracy of various over-limit value.

Citation Download Citation

Junhua Liu, Yong Zhang, Yonghuai Zhang, and Ming Chen "Cross sensitivity reduction of gas sensors using genetic algorithm neural network", Proc. SPIE 4201, Optical Methods for Industrial Processes, (13 February 2001); https://doi.org/10.1117/12.417392

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