머신러닝 기반의 제수밸브 누수 진단 및 압력차를 활용한 유량 예측 방법론의 개발

서지정보

ㆍ발행기관 : 대한상하수도학회 ㆍ수록지정보 : 상하수도학회지 / 37권 / 3호
ㆍ저자명 : 이수민, 정광준, 김현준

목차

1. 서 론
2. 연구 방법 혹은 재료 및 실험방법
2.1 제수밸브의 누수 진단
2.2 기계학습 기반의 제수밸브 누수 진단
2.3 제수밸브를 통한 유량의 평가
2.4 실험 설계
3. 결 과
3.1 제수밸브의 누수 진단
3.2 유량에 대한 예측력
4. 결 론
사 사

영어 초록

Gate valves are hydraulic components used to shut-off the water flow in water distribution systems. Gate valves may fail owing to various aspects such as leakage through seats, wearing of packing, and corrosion. Because it is considerably challenging to detect valve malfunctioning until the operator identifies a significant fault, failure of the gate valve may lead to a severe accident event associated with water distribution systems. In this study, we proposed a methodology to diagnose the faults of gate valves. To measure the pressure difference across a gate valve, two pressure transducers were installed before and after the gate valve in a pilot-scaled water distribution system. The obtained time-series pressure difference data were analyzed using a machine learning algorithm to diagnose faults. The validation of whether the flow rate of the pipeline can be predicted based on the pressure difference between the upstream and downstream sides of the valve was also performed.

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