%0 Journal Article %A Cody, Roya %A Narasimhan, Sriram %A Tolson, Bryan %D 2017 %T CCWI2017: F47 'ONE-CLASS SVM – LEAK DETECTION IN WATER DISTRIBUTION SYSTEMS' %U https://orda.shef.ac.uk/articles/journal_contribution/CCWI2017_F47_ONE-CLASS_SVM_LEAK_DETECTION_IN_WATER_DISTRIBUTION_SYSTEMS_/5363959 %R 10.15131/shef.data.5363959.v1 %2 https://orda.shef.ac.uk/ndownloader/files/9218467 %K CCWI2017 %K One Class SVM %K Water Distribution System %K Dry Barrel Fire Hydrant Mounted Sensor %K Civil Engineering not elsewhere classified %X Acoustic leak detection in water distributions systems has been reviewed and validated for decades in various laboratory and field settings. However, the existing systems rely heavily on detailed knowledge of the pipe system, an assumption of ideal conditions, as well as direct access to infrastructure pipelines. This paper presents an experimental investigation that addresses the need of minimally invasive water distribution monitoring in cold climates. Monitoring in cold climates is achieved with a permanent dry barrel hydrant mounted passive sensor system. The sensor system sits within the water column while still being accessible via the hydrant. Lab tests utilize a retrofitted hydrant and pipe system. Experiments show the effectiveness of using fire hydrant mounted sensors in leak detection. Acoustic signals due to simulated leaks are measured, and a one-class support vector machine (OCSVM) classification methodology is applied. Results showed that a simulated leak can be detected with a 97% classification accuracy.
%I The University of Sheffield