Fast and Robust gas identification system using an integrated gas sensor technology and Gaussian mixture models

Sofiane Brahim-Belhouari, Amine Bermak, Minghua Shi, Philip Ching Ho Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

32 Citations (Scopus)

Abstract

Among the most serious limitations facing the success of future consumer gas identification systems are the drift problem and the real-time detection due to the slow response of most of today's gas sensors. This paper shows that the combination of an integrated sensor array and a Gaussian mixture model permits success in gas identification problems. An integrated sensor array has been designed with the aim of combustion gases identification. Our identification system is able to quickly recognize gases with more than 96% accuracy. Robust detection is introduced through a drift counteraction approach based on extending the training data set using a simulated drift.
Original languageEnglish
Pages (from-to)1433-1444
Number of pages12
JournalIEEE Sensors Journal
Volume5
Issue number6
DOIs
Publication statusPublished - 1 Dec 2005
Externally publishedYes

Keywords

  • Drift counteraction
  • Fast recognition
  • Gas sensors
  • Gaussian mixture model (GMM)

ASJC Scopus subject areas

  • Instrumentation
  • Electrical and Electronic Engineering

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