Identification of Volatile Organic Liquids by Combining an Array of Fiber-Optic Sensors and Machine Learning.

ABSTRACT: In this paper, we report an array of fiber-optic sensors based on the Fabry-Perot interference principle and machine learning-based analyses for identifying volatile organic liquids (VOLs). Three optical fiber tip sensors with different surfaces were included in the array of sensors to improve the accuracy for identifying liquids: an intrinsic (unmodified) flat cleaved endface, a hydrophobic-coated endface, and a hydrophilic-coated endface. The time-transient responses of evaporating droplets from the optical fiber tip sensors were monitored and collected following the controlled immersion tests of 11 different organic liquids. A continuous wavelet transform was used to convert the time-transient response signal into images. These images were then utilized to train convolution neural netwo

SUBMITTER: Naku W 

PROVIDER: S-EPMC9909791 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature