Redundancy Analysis for Tin Oxide Gas Sensor Array

Abstract

Using gas sensor array is widely accepted to overcome the non-selectivity of a single sensor. For tin oxide gas sensors, the size of array can’t be very large due to the limited number of doping materials. In this paper, our experimental results shows that duplication of the sensors doped by the same metal is an efficient way to improve the selectivity of the array due to the fabrication mismatch of the sensor chip. We also compare two methods of reducing the dimension of gas patterns: removing the sensors providing redundant information in the array and using principle component analysis (PCA). The experimental results shows that when the number of components is too large PCA can be a useful tool to reduce the data dimension.