scholarly journals Optimal pressure sensor placement and assessment for leak location using a relaxed isolation index: Application to the Barcelona water network

2017 ◽  
Vol 63 ◽  
pp. 1-12 ◽  
Author(s):  
Miquel À. Cugueró-Escofet ◽  
Vicenç Puig ◽  
Joseba Quevedo
Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 150
Author(s):  
Sen Peng ◽  
Jing Cheng ◽  
Xingqi Wu ◽  
Xu Fang ◽  
Qing Wu

Pressure sensor placement is critical to system safety and operation optimization of water supply networks (WSNs). The majority of existing studies focuses on sensitivity or burst identification ability of monitoring systems based on certain specific operating conditions of WSNs, while nodal connectivity or long-term hydraulic fluctuation is not fully considered and analyzed. A new method of pressure sensor placement is proposed in this paper based on Graph Neural Networks. The method mainly consists of two steps: monitoring partition establishment and sensor placement. (1) Structural Deep Clustering Network algorithm is used for clustering analysis with the integration of complicated topological and hydraulic characteristics, and a WSN is divided into several monitoring partitions. (2) Then, sensor placement is carried out based on burst identification analysis, a quantitative metric named “indicator tensor” is developed to calculate hydraulic characteristics in time series, and the node with the maximum average partition perception rate is selected as the sensor in each monitoring partition. The results showed that the proposed method achieved a better monitoring scheme with more balanced distribution of sensors and higher coverage rate for pipe burst detection. This paper offers a new robust framework, which can be easily applied in the decision-making process of monitoring system establishment.


2021 ◽  
Author(s):  
Caroline Blocher ◽  
Filippo Pecci ◽  
Ivan Stoianov

Abstract Hydraulic model-based leak (burst) localisation in water networks is a challenging problem due to uncertainties, the limited number of hydraulic measurements, and the wide range of leak properties. In this study, we investigate the use of prior assumptions to improve the leak localisation in the presence of model uncertainties. For example, 𝓁2-regularisation relies on the assumption that the Euclidean norm of the leak coefficient vector should be minimised. This approach is compared with a method based on the sensitivity matrix, which assumes the existence of only a single leak. We show that while applying the sensitivity matrix often yields a better estimate of the leak location in single leak scenarios, the 𝓁2-regularisation successfully identifies a leak search area for pinpointing the accurate leak location. Furthermore, we demonstrate that the additional error introduced by a quadratic approximation of the Hazen-Williams formula for the solution of the localisation problem is negligible given the uncertainties in Hazen-Williams resistance coefficients in operational water network models.


Sensors ◽  
2013 ◽  
Vol 13 (11) ◽  
pp. 14984-15005 ◽  
Author(s):  
Myrna Casillas ◽  
Vicenҫ Puig ◽  
Luis Garza-Castañón ◽  
Albert Rosich

2020 ◽  
Vol 516 ◽  
pp. 56-71 ◽  
Author(s):  
Mohammad Sadegh Khorshidi ◽  
Mohammad Reza Nikoo ◽  
Narges Taravatrooy ◽  
Mojtaba Sadegh ◽  
Malik Al-Wardy ◽  
...  

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