Detecting leaks through AMR data analysis

Author:

Claudio K.1,Couallier V.2,Leclerc C.1,Le Gat Y.3,Litrico X.1,Saracco J.4

Affiliation:

1. LyRE (Lyonnaise des Eaux), 91 rue Paulin, F-33000 Bordeaux, France

2. Institut de Mathématiques de Bordeaux, 351 cours de la Libération, F-33405 Talence, France

3. IRSTEA Bordeaux, team REBX, 50 av. de Verdun, F-33612 Cestas, France

4. INRIA Bordeaux Sud-Ouest, team CQFD, 200 av. de la Vieille Tour, F-33405 Talence, France

Abstract

Automatic meter reading (AMR) provides real-time consumption data, enabling to collect a huge amount of information about daily, even hourly, consumptions. It is then easy to assess lost volumes on the network, using supplied volumes information. However, because of the multiple components of water losses, the metering and calculation inaccuracies, the occurrence of new (detectable) leaks is hard to detect. Therefore this paper aims at proposing a user-friendly statistical tool that helps to quickly and reliably detect new leakage occurrence. The use of process control chart (like exponential weighted moving average) enables us to detect changes in the water loss time series, in particular, a new leak occurrence.

Publisher

IWA Publishing

Subject

Water Science and Technology

Reference14 articles.

1. Applying minimum night flow to estimate water loss using statistical modelling: A case study in Kinta Valley, Malaysia;Alkasseh;Water Resources Management,2013

2. Leakage estimation in water networks based on two categories of night-time users: a case study of a developing country network;Amoatey;Water Science & Technology: Water Supply,2014

3. Consumption estimation with a partial automatic meter reading deployment;Claudio;Water Science and Technology: Water Supply,2015

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