Journal of the Korean Society of Visualization (한국가시화정보학회지)

The Korean Society of Visualization (한국가시화정보학회)
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Development of AI oxygen temperature measurement technology using hyperspectral optical visualization technology

초분광 광학가시화 기술을 활용한 인공지능 산소온도 측정기술 개발

  • Jeong Hun Lee (Division of Mechanical Engineering, Korea Maritime and Ocean University) ;
  • Bo Ra Kim (Division of Mechanical Engineering, Korea Maritime and Ocean University) ;
  • Seung Hun Lee (Division of Mechanical Engineering, Korea Maritime and Ocean University) ;
  • Joon Sik Kim (Division of Mechanical Engineering, Korea Maritime and Ocean University) ;
  • Min Yoon (Division of Mechanical Engineering, Korea Maritime and Ocean University) ;
  • Gyeong Rae Cho (Busan Industry-University Convergence Agency)
  • Received : 2023.02.24
  • Accepted : 2023.03.22
  • Published : 2023.03.31
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Abstract

This research developed a measurement technique that can measure the oxygen temperature inside a high temperature furnace. Instead of measuring only changes in frequency components within a small range used in the existing variable laser absorption spectroscopy, laser spectroscopy technology was used to spread out wavelength of the light source passing through the gas Based on a total of 20,000 image data, research was conducted to predict the temperature of a high-temperature furnace using CNN with black and white images in the form of spectral bands by temperature of 25 to 800 degrees. The optimal model was found through Hyper parameter optimization, R2 score is 0.89, and the accuracy of the test data is 88.73%. Based on this research, it is expected that concentration measurement and air-fuel ratio control technology can be applied.

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Acknowledgement

본 연구는 2023년 산업통상자원부 및 산업기술평가관리원(KEIT)의 지원(No.20014988)을 받아 수행되었습니다.

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