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Optimal filter design at the semiconductor gas sensor by using genetic algorithm  

Kong, Jung-Shik (Department of Mechanical Convergence Engineering, Induk University)
Publication Information
Design & Manufacturing / v.16, no.1, 2022 , pp. 15-20 More about this Journal
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 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.
Keywords
Semiconductor Gas Sensor; Optimal Gain; Genetic Algorithm; Temperature Sensor; Low Pass Filter;
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