• 제목/요약/키워드: 응집제 투입률

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K-means 알고리즘과 GBR 알고리즘을 이용한 정수장 응집제 투입률 결정 기법 (Determination of coagulant input rate in water purification plant using K-means algorithm and GBR algorithm)

  • 김진영;강복선;정회경
    • 한국정보통신학회논문지
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    • 제25권6호
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    • pp.792-798
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    • 2021
  • 본 논문에서는 인공지능 기반의 빅데이터 분석과 예측을 통하여 정수장의 공정 중 약품투입곤정에서 응집제 투입률을 결정하는 알고리즘을 도출하였다. 또한, 빅데이터 기술 및 인공지능 알고리즘 적용 방법에 대한 분석 및 기존의 학문적, 기술적 자료를 검토하여 유사 분야 적용 사례를 분석 검토하였다. 이를 통한 최적 응집제 투입률 제시를 목표로 운영 근무자의 의사결정 패턴을 입력 변수와 출력변수의 관계 패턴으로 학습한 후 학습된 패턴을 실제 응집제 주입 공정에 적용하여 침전수 탁도가 목표치에 근사한 일정 수준을 유지할 수 있도록 운영이 가능하였다. 데이터 범위 산정과 전처리를 거친 변수를 선정하여 알고리즘 수행을 준비한 후 군집화와 분류 알고리즘을 적용하여 알고리즘 수행과 결과에 대한 피드백을 반복하여 학습을 진행하였다.

Fuzzy Neural Network에 응집제 투입률의 자동결정 (Automatic Determination of Coagulant Dosing Rate Using Fuzzy Neural Network)

  • 정우섭;오석영
    • 한국정밀공학회지
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    • 제14권1호
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    • pp.101-107
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    • 1997
  • Recently, as the raw water quality becomes to be polluted and the seasonal and local variation of water quality becomes to be severe, an exact control of coagulant dosing have been required in the water treat- ment plant. The amounts of coagulant is related to the raw water quality such as turbidity, alkalinity, water temperature, pH and edectrical conductivity. However the process of chemical reaction has not been clarified so far, so the dosing rate has been decided by jar-test, which is taken one or two hours. For the sake of this coagulant dosing control, fuzzy neural network to fuse fuzzy logic and neural network was proposed, and the scheme was applied to automatic determination of coagulant dosing rate. This controller can automatically identify the if-then rules and tune the membership functions by utilizing expert's cintrol data. It is shown that determination of coagulant dosing rate according to real time sensing of water quality is very effect.

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자기조직형 Fuzzy Neural Network에 의한 응집제 투입률 자동제어 (Automatic Control of Coagulant Dosing Rate Using Self-Organizing Fuzzy Neural Network)

  • 오석영;변두균
    • 제어로봇시스템학회논문지
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    • 제10권11호
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    • pp.1100-1106
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    • 2004
  • In this report, a self-organizing fuzzy neural network is proposed to control chemical feeding, which is one of the most important problems in water treatment process. In the case of the learning according to raw water quality, the self-organizing fuzzy network, which can be driven by plant operator, is very effective, Simulation results of the proposed method using the data of water treatment plant show good performance. This algorithm is included to chemical feeder, which is composed of PLC, magnetic flow-meter and control valve, so the intelligent control of chemical feeding is realized.