Alcoholic Gas Discrimination Using 32-Channel Fiber-Optic Sensor Array

摘要

This paper describes the alcoholic gas discrimination experiment using an artificial neural network pattern recognition technique and dye absorbance spectra patterns from a 32-channel fiber-optic sensor array with different dye coating, whose absorption spectra change with alcoholic gas exposure. The 32-channel absorption spectrra were simultaneously measured by using 13 band-pass filters and 32 photodiodes, and data-processed by the pattern recogni- tion method.