International Journal of Fuzzy Logic and Intelligent Systems

  • 제7권4호
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  • Pages.279-284
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  • 2007
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  • 1598-2645(pISSN)
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  • 2093-744X(eISSN)
한국지능시스템학회 (Korean Institute of Intelligent Systems)
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On-line Diagnosis System with Learning Bayesian Networks for fsEBPR

  • Cheon, Seong-Pyo (Department of Electrical Engineering, Pusan National University) ;
  • Kim, Sung-Shin (Department of Electrical Engineering, Pusan National University)
  • 발행 : 2007.12.01
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초록

Nowadays, due to development of automatic control devices and various sensors, one operator can freely handle several remote plants and processes. Automatic diagnosis and warning systems have been adopted in various fields, in order to prepare an operator's absence for patrolling plants. In this paper, a Bayesian networks based on-line diagnosis system is proposed for a wastewater treatment process. Especially, the suggested system is included learning structure, which can continuosly update conditional probabilities in the networks. To evaluate performance of proposed model, we made a lab-scale five-stage step-feed enhanced biological phosphorous removal process plant and applied on-line diagnosis system to this plant in the summer.

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참고문헌

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