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Optimal Filter Design at the Semiconductor Gas Sensor by Using Genetic Algorithm

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초록

This paper is about elimination the situation in which gas sensor data becomes inaccurate due to temperature control when a semiconductor gas sensor is driven. Recently, interest in semiconductor gas sensors is high because semiconductor sensors can be driven with small and low power. Although semiconductor-type gas sensors have various advantages, there is a problem that they must operate at high temperatures. First temperature control was configured to adjust the temperature value of the heater mounted on the gas sensor. At that time, in controlling the heater temperature, gas sensor data are fluctuated despite supplying same gas concentration according to the temperature controlled. To resolve the this problem, gas and temperature are extracted as a data. And then, a relation function is constructed between gas and temperature data. At this time, it is included low pass filter to get the stable data. In this paper, we can find optimal gain and parameters between gas and temperature data by using genetic algorithm.

Abstract

This paper is about elimination the situation in which gas sensor data becomes inaccurate due to temperature control when a semiconductor gas sensor is driven. Recently, interest in semiconductor gas sensors is high because semiconductor sensors can be driven with small and low power. Although semiconductor-type gas sensors have various advantages, there is a problem that they must operate at high temperatures. First temperature control was configured to adjust the temperature value of the heater mounted on the gas sensor. At that time, in controlling the heater temperature, gas sensor data are fluctuated despite supplying same gas concentration according to the temperature controlled. To resolve the this problem, gas and temperature are extracted as a data. And then, a relation function is constructed between gas and temperature data. At this time, it is included low pass filter to get the stable data. In this paper, we can find optimal gain and parameters between gas and temperature data by using genetic algorithm.

참고문헌 (7)

  1. 김종구, "다공성 및 아민 작용기에 따른 탄소나노섬유의 CO2 감응특성", 공업화학, 23(1), pp.47~52 (2012), 한국공업화학회
  2. S. H. Lee, "An Increase in gas Sensitivity and Recovery of an MWCNT-based gas sensor system in reponse to an electric field", 497(4-6), pp.191~195 (2010)
  3. Gerhard Wiegleb and, "Semiconductor gas sensor for detecting NO and CO traces in ambient air of road traffic", Sensors and Actuators B: Chemical, 17(2), pp.93~99 (1994)
  4. David E. Williams, "Semiconducting oxides as gas-sensitive resistors", Sensors and Actuators B:Chemical, 57(1-3), pp.1~16 (1999)
  5. 한창호, "주기성 부하를 갖는 DC모터 속도제어 시스템의 SMC와 PI제어의 강인성 비교", 동력시스템공학회지, 22(3), pp.23~31 (2018), 한국동력기계공학회[DOI]
  6. J.E. Beasley, "A genetic algorithm for the set covering problem", European Journal of Operational Research, 94(2), pp.392~404 (1996)
  7. Manosij Ghosh, "Binary Genetic Swarm Optimization: A Combination of GA and PSO for Feature Selection", Journal of Intelligent Systems, 29(1), pp.1598~1610 (2020)

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