A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
A review of data-driven approaches for burst detection in water distribution systems
This study focuses on data-driven approaches for burst detection and classifies them into three categories: classification method, prediction-classification method and statistical method. The performance of these methods is discussed. By analysing uncertainty in burst detection, this paper revealed that non-stationary monitoring data and limitations present in these methods challenge the reliability of detection results. Data pre-processing and probabilistic solutions to deal with the uncertainty are summarised. From these findings and discussions, this paper concludes and recommends that: a) data-driven approaches are promising in real-life burst detection and reducing false alarms is an important issue; b) more comprehensive performance evaluation might be necessary, in particular regarding detectable burst size; c) further research on new methods employing multivariate analysis and a new category based on clustering analysis would be beneficial to tackle uncertainty; d) more focus on the use of pressure data might facilitate burst location and reduce investment in burst detection.
A review of data-driven approaches for burst detection in water distribution systems
This study focuses on data-driven approaches for burst detection and classifies them into three categories: classification method, prediction-classification method and statistical method. The performance of these methods is discussed. By analysing uncertainty in burst detection, this paper revealed that non-stationary monitoring data and limitations present in these methods challenge the reliability of detection results. Data pre-processing and probabilistic solutions to deal with the uncertainty are summarised. From these findings and discussions, this paper concludes and recommends that: a) data-driven approaches are promising in real-life burst detection and reducing false alarms is an important issue; b) more comprehensive performance evaluation might be necessary, in particular regarding detectable burst size; c) further research on new methods employing multivariate analysis and a new category based on clustering analysis would be beneficial to tackle uncertainty; d) more focus on the use of pressure data might facilitate burst location and reduce investment in burst detection.
A review of data-driven approaches for burst detection in water distribution systems
Wu, Yipeng (author) / Liu, Shuming (author)
Urban Water Journal ; 14 ; 972-983
2017-10-21
12 pages
Article (Journal)
Electronic Resource
English
A review of data-driven approaches for burst detection in water distribution systems
| Online Contents | 2017
A review of data-driven approaches for burst detection in water distribution systems
| Online Contents | 2017
Burst Detection and Location in Water Distribution Systems
| British Library Conference Proceedings | 2011
Evaluation of data driven models for pipe burst prediction in urban water distribution systems
| Taylor & Francis Verlag | 2019