Title :
Optical Fiber Sensors Array to Identify Beverages by Their Odor
Author :
Elosua, Cesar ; Bariain, Candido ; Luquin, Asuncion ; Laguna, Mariano ; Matias, Ignacio R.
Author_Institution :
Dept. of Electr. & Electron. Eng., Public Univ. of Navarra, Pamplona, Spain
Abstract :
Four optical fiber sensors have been grouped in an array which is able to distinguish odors of different drinks. The sensing materials employed have been deposited onto optical fibers following the electrostatic self assembly method. The responses have been characterized in terms of reflected optical power; more specifically, the dynamic range and the recovery of each device have been used to discriminate between the samples. Data mining techniques based on the combination of principal component analysis and artificial neural networks are performed. The final system is trained to distinguish between grape juice, wine, and vinegar by using a set of one hundred samples of each one. Furthermore, the array can be located at up to 6 km away from the optical header, offering the possibility of in situ measurements.
Keywords :
array signal processing; beverages; chemical sensors; data mining; electronic noses; fibre optic sensors; neural nets; principal component analysis; remote sensing; self-assembly; artificial neural networks; beverages; data mining; dynamic range; electrostatic self assembly; grape juice; odor; optical fiber sensors array; optical header; principal component analysis; vinegar; wine; Arrays; Chemicals; Optical fiber sensors; Optical fibers; Array signal processing; chemical sensors; multiplexing; optical fiber sensors; remote sensing; wavelength division;
Journal_Title :
Sensors Journal, IEEE
DOI :
10.1109/JSEN.2012.2215023