Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Determination of coagulant input rate in water purification plant using K-means algorithm and GBR algorithm

K-means 알고리즘과 GBR 알고리즘을 이용한 정수장 응집제 투입률 결정 기법

  • Kim, Jinyoung (Department of Computer Engineering, Paichai University) ;
  • Kang, Bokseon (Department of Computer Engineering, Paichai University) ;
  • Jung, Hoekyung (Department of Computer Engineering, Paichai University)
  • Received : 2021.05.10
  • Accepted : 2021.06.02
  • Published : 2021.06.30
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Abstract

In this paper, an algorithm for determining the coagulant input rate in the drug-injection tank during the process of the water purification plant was derived through big data analysis and prediction based on artificial intelligence. In addition, analysis of big data technology and AI algorithm application methods and existing academic and technical data were reviewed to analyze and review application cases in similar fields. Through this, the goal was to develop an algorithm for determining the coagulant input rate and to present the optimal input rate through autonomous driving simulator and pilot operation of the coagulant input process. Through this study, the coagulant injection rate, which is an output variable, is determined based on various input variables, and it is developed to simulate the relationship pattern between the input variable and the output variable and apply the learned pattern to the decision-making pattern of water plant operating workers.

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.

Keywords

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