Burst Detection in Water Networks Using Principal Component Analysis

Abstract

The following work presents a multivariate statistical technique applied to the control of water inflows into district metering areas (DMA) of urban networks. This technique, called Principal Component Analysis (PCA), allows for a sensitive and quick analysis of the inflows into a DMA without hassling mathematical algorithms. PCA technique simplifies the original set of flow rate data recorded by the SCADA system, synthesizing the most significant information into a statistical model which is able to explain most of the behaviour of the water distribution network. PCA technique also allows for the establishment of control charts that help system operators in the identification of anomalous behaviours regarding water use, bursts or illegal connections. The described technique has been proved to offer high detection sensitivity to bursts or other unexpected consumptions.