Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 561269
Title Detecting pipe bursts using Heuristic and CUSUM methods
Author(s) Bakker, M.; Jung, D.; Vreeburg, J.; De Roer, M. Van; Lansey, K.; Rietveld, L.
Source Procedia Engineering 70 (2014). - ISSN 1877-7058 - p. 85 - 92.
Event 12th International Conference on Computing and Control for the Water Industry, CCWI 2013, Perugia, 2013-09-02/2013-09-04
DOI https://doi.org/10.1016/j.proeng.2014.02.011
Department(s) Environmental Technology
Publication type Refereed Article in a scientific journal
Publication year 2014
Keyword(s) Demand forecasting - Pipe burst detection - SPC methods
Abstract

Pipe bursts in a drinking water distribution system lead to water losses, interruption of supply, and damage to streets and houses due to the uncontrolled water flow. To minimize the negative consequences of pipe bursts, an early detection is necessary. This paper describes a heuristic burst detection method, which continuously compares forecasted and measured values of the water demand. The forecasts of the water demand were generated by an adaptive water demand forecasting model. To test the method, a dataset of five years of water demand data in a supply area in the Western part of the Netherlands was collected. The method was tested on a subset of the data (only the winter months) in which 9 (larger) burst events were reported. The detection probability for the reported bursts was 44.4%, at an acceptable rate of false alarms of 5.0%. The results were compared with the CUSUM method, which is a general statistical process control (SPC) method to identify anomalies in time series. The heuristic and CUSUM methods generated comparable results, although rate of false alarm for the heuristic method was lower at the same detection probability.

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