An optical artificial nose system for odor classifications based on LED arrays

Abstract

Optical electronic nose (olfactory sensing) technologies have recently become a convenient technique to identify the quality of food and beverage products based on the odor classification. In this paper, we reported an optical-based electronic nose system consisting of thin-film sensing materials, array of light emitting diode (LED), photo-detector and pattern recognition program. The organic mixtures thin film gas sensor was prepared by spin coating of Zinc-2,9,16,23- tetra- tert-butyl-29H,31H-phthalocyanine (ZnTTBPc), Zinc-5,10,15,20-tetra-phenyl-21H,23H-porphyrin (ZnTPP) and manganese(III)-5,10, 15,20-tetra-phenyl-21H,23H-porphyrin chloride (MnTPPCl) onto a clean glass substrate. The electronic nose system was developed by using the low-cost LED array as a light source. Then the light intensity that is transmitted through the organic thin film during the experiment was detected by the color light to frequency converter device (photo-detector). The ability of this system was tested by using volatile organic compound (VOCs) vapors such as methanol, ethanol, and isopropanol. Principal component analysis (PCA) has been used as the pattern recognition for this electronic nose system. The result confirms that the sensing layer that composed of the three types of organic compounds described the groups of chemical vapors by using the array of LED. © 2011 IEEE.