제어로봇시스템학회:학술대회논문집

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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An Embedded system for real time gas monitoring using an ART2 neural network

  • Cho, Jung-Hwan (School of Electrical Engineering and Computer Science, Kyungpook National University) ;
  • Shim, Chang-Hyun (Sense & Sensor Co., Ltd. Technopark of Kyungpook National University) ;
  • Lee, In-Soo (School of Electronics and Electrical Engineering, Sangju National University) ;
  • Lee, Duk-Dong (School of Electrical Engineering and Computer Science, Kyungpook National University) ;
  • Jeon, Gi-Joon (School of Electrical Engineering and Computer Science, Kyungpook National University)
  • Published : 2003.10.22
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Abstract

We propose a real time gas monitoring system for classifying various gases with different concentrations. Using thermal modulation of operating temperature of two sensors, we extract patterns of gases from the voltage across the load resistance. We adopt the relative resistance as a pre-processing method and an ART2 neural network as a pattern recognition method. The proposed method has been implemented in a real time embedded system with tin oxide gas sensors, TGS 2611, 2602 and an MSP430 ultra-low power microcontroller in the test chamber.

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