Publication date:
07/27/2010
Information about the environment is essential for the survival of every living being,
since it determines the way to react with respect to external inputs. In the case of
humans, this information is collected through the five senses; sight, hearing, touch,
smell and taste. Sight, hearing and smell senses are considered specially interesting
because of their ability to get external information without direct interaction with
the sources. Sight is probably the most developed sense in humans, followed closely
by hearing. On the contrary, smell has always been considered the most primitive
and less important of those three senses, and was an almost total mystery until a
few years ago. Recently, in 2004, Dr. Richard Axel and Dr. Linda Buck shared the
Nobel Prize in medicine for their discoveries of odorant receptors and the organization
of the olfactory system, since then, studies on the smell and human olfactory system
have received a new interest.
With the aim of extending our senses abilities of obtaining information about our
surroundings, some devices have been developed which are inspired by the biological
mechanisms of the senses. Examples of such devices are well known and of very
extended use, like video cameras used for security issues in which image recognition
can be implemented (sight), or sound recording with speech recognition (hearing).
Relating smell, an instrument named electronic nose was proposed in 1982 by Persaud
and Dodd [1] to differentiate odours. Electronic noses were very promising for
many qualitative and quantitative applications, since they were expected to provide
characteristics such as being of small size, low cost, fast and easy to use. These
features are specially interesting for on-field applications, compared to other wellestablished
instruments for gas/volatiles analysis which are big, heavy, expensive
and difficult to use, though they provide better chemical resolution.
Despite the many potential advantages of the use of electronic noses, nowadays,
more than 25 years after the first device, this instrument is not massively present
on the market. The main reason lies in the sensing area of the instrument, which
exhibits poor selectivity and bad stability. The chemical gas sensors used in electronic
noses present problems like cross sensitivities, time instability, dependence
on previous gas exposures, etc. Therefore, instruments based on these sensors are
not robust and do not give enough reproducible results. The nature of the problems
that influence chemical gas sensors is mainly technological, but affect sensors
of all state of the art technologies, though to different degrees. These deficiencies
can be mostly overcome as more research is made on improving fabrication process
or developing new technologies. However, while gas sensors technologies are being
improved, statistical signal processing can help to mathematically compensate, or
at least to reduce, the effect those mentioned issues have on the sensors responses
before pattern recognition is carried out.
The aim of this thesis is to explore the robustness of some sensor operation methods,
and to propose the use of statistical signal processing techniques to correct
or compensate sensors responses affected by specific problems, such as sensor drift
and failure of one or more sensors in the array. This document is organized in five
chapters. In the first one, the concepts of machine olfaction and electronic noses
are revised, as well as the main problems that the instrument presents. Specially,
evidence of specific issues studied in this thesis and state of the art on solutions by
signal processing techniques are presented in this chapter. Concepts and definitions
of robustness are given in chapter two. In the third chapter, the aim of this dissertation
is detailed. Then, chapter fourth explains the work made and presents the
papers which shows many, but not all, of the results obtained during these years of
work. Finally, conclusions are given in chapter five.
