DOI QR코드

DOI QR Code

병렬구조 TSK 퍼지 모델을 이용한 선박용 기름배출 감시장치의 실시간 기름농도 예측모델

On-line Prediction Model of Oil Content in Oil Discharge Monitoring Equipment Using Parallel TSK Fuzzy Modeling

  • 백경동 (부산대학교 전자전기공학부) ;
  • 조재우 (부산대학교 전자전기공학부) ;
  • 최문호 (부산대학교 전자전기공학부) ;
  • 김성신 (부산대학교 전자전기공학부)
  • 발행 : 2010.01.01

초록

The oil tanker ship over 150GRT must equip oil content meter which satisfy requirements of revised MARPOL 73/78. Online measurement of oil content in complex samples is required to have fast response, continuous measurement, and satisfaction of ${\pm}10ppm$ or ${\pm}10%$ error in this field. The research of this paper is to develop oil content measurement system using analysis of light transmission and scattering among turbidity measurement methods. Light transmission and scattering are analytical methods commonly used in instrumentation for online turbidity measurement of oil in water. Gasoline is experimented as a sample and the oil content approximately ranged from 14ppm to 600ppm. TSK Fuzzy Model may be suitable to associate variously derived spectral signals with specific content of oil having various interfering factors. Proposed Parallel TSK Fuzzy Model is reasonably used to classify oil content in comparison with other models. Those measurement methods would be effectively applied and commercialized to oil content meter that is key components of oil discharge monitoring control equipment.

참고문헌

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