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Probabilistic gas quantification with MOX sensors in open sampling systems: a gaussian process approach
University of Málaga. (Machine Perception and Intelligent Robotics (MAPIR))
Örebro University, School of Science and Technology. (SS Research Centre, Mobile Robotics and Olfaction Lab)ORCID iD: 0000-0003-0217-9326
University of Almería.
University of Málaga. (Machine Perception and Intelligent Robotics (MAPIR))
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2013 (English)In: Sensors and actuators. B, Chemical, ISSN 0925-4005, E-ISSN 1873-3077, Vol. 188, 298-312 p.Article in journal (Refereed) Published
Abstract [en]

Gas quantification based on the response of an array of metal oxide (MOX) gas sensors in an Open Sampling System is a complex problem due to the highly dynamic characteristic of turbulent airflow and the slow dynamics of the MOX sensors. However, many gas related applications require to determine the gas concentration the sensors are being exposed to. Due to the chaotic nature that dominates gas dispersal, in most cases it is desirable to provide, together with an estimate of the mean concentration, an estimate of the uncertainty of the prediction. This work presents a probabilistic approach for gas quantification with an array of MOX gas sensors based on Gaussian Processes, estimating for every measurement of the sensors a posterior distribution of the concentration, from which confidence intervals can be obtained. The proposed approach has been tested with an experimental setup where an array of MOX sensors and a Photo Ionization Detector (PID), used to obtain ground truth concentration, are placed downwind with respect to the gas source. Our approach has been implemented and compared with standard gas quantification methods, demonstrating the advantages when estimating gas concentrations.

Place, publisher, year, edition, pages
Elsevier, 2013. Vol. 188, 298-312 p.
Keyword [en]
Gas quantification, Open Sampling System, MOX sensors, Gaussian Processes
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-30220DOI: 10.1016/j.snb.2013.06.053ISI: 000326345600040Scopus ID: 2-s2.0-84881300519OAI: oai:DiVA.org:oru-30220DiVA: diva2:641025
Note

Funding agency:

Regional Government of Andalucia 

European Union (FEDER) P08-TEP-4016 

Available from: 2013-08-15 Created: 2013-08-15 Last updated: 2017-12-06Bibliographically approved

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Lilienthal, Achim J.Trincavelli, Marco

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