Detection of gas/odor based on quartz crystal microbalance sensors and fuzzy similarity measure
In this research, an array of six Quartz Crystal Microbalance sensors (QCM) using fuzzy similar measurement is proposed to recognize different gases and the percentage of those gases in a mixed gas. The experiment suggests three different gases, oxygen, helium, and argon as test gases and the nitrogen as the reference gas. Six QCMs in this array are coated respectively with six different specific polymers that are selected based on Linear Solvation Energy Relationship (LSER) method, in order to absorb gas molecules so as to recognize responses of resonant frequency changes from QCMs. Testing with different gases results in different responding patterns from QCMs array, which means the possibility of differentiating a gas from the others by comparing the responding pattern of the gas with other patterns, e.g. the pattern of oxygen is different from the pattern of helium and argon. Based on the pattern recognition, an idea of perceiving a correct percentage of a specific gas in a mixed gas is also introduced; this idea is realized by comparing response patterns with a diversity of percentage of the same gas. Fuzzy similarity comparison provides an alternative way to deal with the issue of pattern recognition. The most crucial part of fuzzy similarity comparison is to establish a database of response patterns which is able to recognize not only the type of the gas detected, but also the percentage of the gas in the air.
Lo, Yi-Chen, "Detection of gas/odor based on quartz crystal microbalance sensors and fuzzy similarity measure" (2009). ETD Collection for University of Texas, El Paso. AAI1461159.