Abstract
Recently, the size of the chemical industry has been growing as well as investing a lot of time and resources to develop core technologies and cultivate human resources. As a result, the handling of chemicals is increasing and the risks are increasing. In particular, there is always the problem of the occurrence of chemical accidents due to the failure of control or management. To prevent this, a disaster detection system using sensors is actively under study. However, the gas sensor among the disaster detection sensors is malfunction due to the influence of the temperature and the humidity. Therefore, in this paper, we collect correlation data of temperature sensor and gas sensor to prevent this. After confirming the correlation through correlation analysis, we calculate regression coefficient by regression analysis and obtain regression equation that can extract sample values of gas sensor data and temperature sensor data. Through this formula, a threshold value that can detect the error value of the gas sensor data is obtained and applied to the decision tree to design a system that can detect the malfunction of the gas sensor according to the temperature change.
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Acknowledgment
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A3B03036130)
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Yoon, KS., Lee, SH., Lee, JP., Lee, JK. (2019). Designing System Model to Detect Malfunction of Gas Sensor in Laboratory Environment. In: Lee, R. (eds) Computational Science/Intelligence & Applied Informatics. CSII 2018. Studies in Computational Intelligence, vol 787. Springer, Cham. https://doi.org/10.1007/978-3-319-96806-3_9
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DOI: https://doi.org/10.1007/978-3-319-96806-3_9
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