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Sensor State Isolation for Wastewater Based on Influent Characteristics Methodology

물질수지분석을 이용한 하수처리장 유입수질 측정 센서의 상태 진단

  • Baek Jiwon (UnU Inc.) ;
  • Kim Jongrack (UnU Inc.) ;
  • You Kwangtae (UnU Inc.) ;
  • Kim Yejin (Department of Fire and Disaster Prevention, Catholic University of Pusan)
  • 백지원 (주식회사 유앤유) ;
  • 김종락 (주식회사 유앤유) ;
  • 유광태 (주식회사 유앤유) ;
  • 김예진 (부산가톨릭대학교 소방방재학과)
  • Received : 2024.02.29
  • Accepted : 2024.06.20
  • Published : 2024.07.30

Abstract

Wastewater treatment plants are constantly exposed to influent wastewater that is constantly changing. This poses a major challenge to the operation of the plants. It is crucial to have a rapid and accurate measurement of the influent concentrations of wastewater in order to maintain and optimize treatment performance, as well as to develop energy-saving strategies. While laboratory measurements provide the highest accuracy in determining influent water quality, they are inevitably time-consuming procedures. In order to cope with the ongoing disturbances from wastewater influent, absorption-based optical measuring instruments have been developed. These instruments can detect the influent water quality in a short amount of time, improving their practicality and reliability. However, when these optical measuring instruments malfunction, the accuracy of the measured values decreases, leading to unreasonable operation of the treatment plant. This paper proposes a method for detecting anomalies in optical water quality measurement devices. The Harmony Search algorithm is used to validate the measured water quality values and detect abnormalities such as contamination or physical anomalies in the measurement apparatus. To assess the performance of the developed algorithm in detecting anomalies, validation was conducted by installing it in a field-scale wastewater treatment plant. The results consistently showed that the developed fault detection method for optical water quality measurements equipment provided acceptable results for normal, temporary abnormal, and long-term abnormal conditions.

Keywords

Acknowledgement

This research was supported by the Korea Environment Industry & Technology Institute(KEITI) through the "Prospective Green Technology Innovation Project" (No.2021003160003), funded by the Korea Ministry of Environment (MOE). This research was also supported by Korea Water Cluster through 2022 Project for Active and Digitalization of Water Technology(2022200007).

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