Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
The present work describes an algorithm to enhance selectivity of metal oxide
(MOX) gas sensors. The main objective is to improve gas discrimination
performance of MOX sensor using a temperature modulation combined with
phase space method. Our aim is to achieve a very good gas discrimination performance
based on a fragment of sensor signal, rather than using the response
of sensor for entire modulation signal.
The basic principle behind this thesis work is that investigating in sensor
response and extracting a segment with high class separability from a full modulation
cycle of sensor response. The fragment of sensor signal is obtained by
variable sliding window. A segment that gives more separable classes is taken
for discriminating between a set of given analytes. In this work we demonstrate
the developed algorithm with a single, commercially available MOX sensor, Figaro
TGS 2620, which is temperature modulated with a sinusoidal waveform.
2012. , 79 p.