Urban Water Journal · 2018 · 60 citations · 24 references
ComputingWater Resources ManagementMachine LearningTime Series AnalysisWater Resources EngineeringAnomaly DetectionFault DetectionFlow SensorsLeak DetectionPipeline SystemsFault Diagnosis In PipelinesPipe Leak DetectionPipeline Condition MonitoringPipeline Leak DetectionPipelinesSensor-based Anomaly DetectionWater Leak DetectionWater Leakage Detection
This paper presents the validation of a novel leak detection method for water distribution pipelines, although it could be applied to any buried pressurized fluid flow pipe. The detection method is based on a relative pressure sensor attached non-invasively to the outside of the pipe combined with temperature difference measurements between the pipe wall and the soil. Moreover, this paper proposes an anomaly detection algorithm, originally developed for monitoring website traffic data, which differentiates a ‘leak’ event from ‘normal’ pressure change events. It is compared to two more commonly used methods based on a fixed threshold and a moving average. The validation of the new system in a field trial over a 6-month period showed that all the known leaks were identified with 98.45% accuracy, with the anomaly detection algorithm performing best, making this system a real contender for leak detection in pipes.
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PIPENETa wireless sensor network for pipeline monitoring
Ivan Stoianov, Lama Nachman, Samuel Madden et al. · 2007 · 468 citations
Engineering, Civil Engineering, Water Resources Management +17
PIPENET: A Wireless Sensor Network for Pipeline Monitoring
Ivan Stoianov, Lama Nachman, Samuel Madden et al. · 2007 · 291 citations
Engineering, Civil Engineering, Water Resources Management +17