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.

Recently, the increased maintenance cost of underground structures due to leakage problems. Also, social issues are discussed in the sink hole caused by the loss of groundwater. For this reason, Leak diagnosis, waterproof and repair of underground structure is important today. So, the aim of this study was the necessity for water leak diagnosis and repair of underground structures.