SAW humidity sensor and an environmental electronic nose system
Tashtoush, Nehad M (1996) SAW humidity sensor and an environmental electronic nose system. PhD thesis, Concordia University.
NQ25915.pdf
A polymer-coated surface-acoustic-wave dual delay line oscillator of 50MHz fundamental frequency has been successfully applied as a humidity sensor. A YZ-cut lithium niobate substrate was used. The polymer (polyXIO) was deposited directly over the substrate or over a metal film on the substrate. A turn-around in the frequency shift and a jump in the attenuation were observed when the polymer was deposited over the substrate directly, and therefore the relative humidity range cannot be covered completely. It appears that depositing the polymer over a metal film eliminates both the turn-around in frequency shift and the jump in the attenuation. Moreover, the curve was smooth and covered the full range of relative humidity, and the change in attenuation was found to be lower than the non-metallized path. The viscoelastic mechanism appears to dominate for the whole range of relative humidity. The sensor was found to be reproducible with a moderate hysteresis effect, of the order of 5%. The sensor appears to have no cross effects from other gases and seems to be highly selective to humidity. This absence of cross effects makes the device a good candidate for humidity measurements in general and to eliminate humidity effects in electronic nose systems. Also, an electronic nose system of four Taguchi Gas Sensors (TGS) was built. It appears that each sensor has a separate response pattern to each gas used in the test (methane, propane, ethylene and ethane), and that the relative humidity affects the behavior of the electronic nose system. The feasibility of discriminating between gases in mixture was demonstrated. The effects of the ambient conditions, especially humidity, temperature, and the concentration of oxygen gas inside the chamber, appears to affect the reproducibility of the system. This results in a non-reproducible output of the sensors which makes it difficult to train the neural network program in order to discriminate between gases at a given value of relative humidity and concentration. Using different kinds of sensors which is more stable under ambient conditions might give more precise results in discriminating between gases and could improve the estimation of the concentration in the mixture.
Concordia University > Faculty of Arts and Science > Physics
Tashtoush, Nehad M
xvi, 133 leaves : ill. ; 29 cm.
Cheeke, David