Over the past decades, the management, calibration and power cost reduction of water pipeline systems have received an increasing attention due to the current environmental concerns and the poor condition of the pipe networks. Effective water system management rests upon the knowledge of current state of a water pipeline system network. For example, blockages in a water pipeline system are often the source of an increase of the costs of pumping. These anomalies must be detected and corrected as early as possible. In this study, an algorithm is developed for detecting blockages by means of pressure transient measurements. The algorithm is a stochastic successive linear estimator which provides statistically best unbiased estimate of partial blockages and quantifies the uncertainty associated with these estimates. We first present the theoretical formulation of the algorithm and then test it with a numerical example.

Detection of partial extended blockages by means of a stochastic successive linear estimator

MASSARI, CHRISTIAN;FERRANTE, Marco;BRUNONE, Bruno;MENICONI, SILVIA
2012

Abstract

Over the past decades, the management, calibration and power cost reduction of water pipeline systems have received an increasing attention due to the current environmental concerns and the poor condition of the pipe networks. Effective water system management rests upon the knowledge of current state of a water pipeline system network. For example, blockages in a water pipeline system are often the source of an increase of the costs of pumping. These anomalies must be detected and corrected as early as possible. In this study, an algorithm is developed for detecting blockages by means of pressure transient measurements. The algorithm is a stochastic successive linear estimator which provides statistically best unbiased estimate of partial blockages and quantifies the uncertainty associated with these estimates. We first present the theoretical formulation of the algorithm and then test it with a numerical example.
2012
9783941492455
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/913541
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