상하수도학회지 제33권 제2호 (p.151-158)

|Research Papers|
폐수의 무단 방류 모니터링을 위한 센서배치 우선지역 결정: 자기조직화지도 인공신경망의 적용

Real-time monitoring sensor displacement for illicit discharge of wastewater: identification of hotspot using the self-organizing maps (SOMs)
키워드 :
Illicit discharge,Self-organizing maps(SOMs),Sensor displacement,Urban drainage,Wastewater monitoring,무단방류,자기조직화지도,센서 배치,도시하수,폐수 모니터링

목차

ABSTRACT
1. 서 론
2. 연구방법
  2.1 대상지역 현황조사
  2.2 수질모니터링 및 분석
  2.3 데이터분석
3. 결과 및 고찰
  3.1 폐수의 수질분석
  3.2 SOM clustering
  3.3 센서의 우선배치지역 결정
4. 결 론
References

초록

Objectives of this study were to identify the hotspot for displacement of the on-line water quality sensors, in order to detect illicit discharge of untreated wastewater. A total of twenty-six water quality parameters were measured in sewer networks of the industrial complex located in Daejeon city as a test-bed site of this study. For the water qualities measured on a daily basis by 2-hour interval, the self-organizing maps(SOMs), one of the artificial neural networks(ANNs), were applied to classify the catchments to the clusters in accordance with patterns of water qualities discharged, and to determine the hotspot for priority sensor allocation in the study. The results revealed that the catchments were classified into four clusters in terms of extent of water qualities, in which the grouping were validated by the Euclidean distance and Davies-Bouldin index. Of the on-line sensors, total organic carbon(TOC) sensor, selected to be suitable for organic pollutants monitoring, would be effective to be allocated in D and a part of E catchments. Pb sensor, of heavy metals, would be suitable to be displaced in A and a part of B catchments.