A review of sensor placement objective metrics for contamination detection in water distribution networks

2015 ◽  
Vol 15 (5) ◽  
pp. 898-917 ◽  
Author(s):  
Shweta Rathi ◽  
Rajesh Gupta ◽  
Lindell Ormsbee

Security of water distribution networks (WDNs) through early warning systems is one of the topics of research over the last two decades to safeguard human health and the environment against accidental and intentional contamination. Several methodologies have been suggested by different researchers for placement of sensors in WDNs which can provide early warning. Owing to the cost of both placing and maintaining the sensors, the number of these must be limited. This constraint makes the sensor deployment locations crucial in early warning systems. In this paper various methodologies suggested for sensor placements have been broadly classified based on the number of performance objectives as single and multi-objective sensor location problems. Various objectives and their significance in the context of sensor placement strategy have been discussed. A complete review of literature is presented to understand complexities in the sensor design problems and to determine the directions in which research is heading. Several challenges for the design of robust sensor network for large WDNs with less computational efforts are discussed and recommendations are presented.

2015 ◽  
Vol 16 (2) ◽  
pp. 493-505 ◽  
Author(s):  
Daniel Hernández Cervantes ◽  
Jesús Mora Rodríguez ◽  
Xitlali Delgado Galván ◽  
Josefina Ortiz Medel ◽  
Martín Rubén Jiménez Magaña

Water distribution networks (WDNs) could present problems of pathogen intrusion that affect the health of consumers. One solution to diminish this risk is to add more disinfectant to the water at the drinking water treatment plant (DWTP). However, this increases the cost of water treatment and may also cause the formation of trihalomethanes. Mexico has the largest bottled water market in the world. Also, most houses are built with individual storage containers due to intermittent service, which generates a greater residence time of the water before use. This paper shows an alternative to guarantee minimum disinfection along WDNs and diminish the use of disinfectant at the DWTP considering the conditions of water consumption and use in Mexico. We propose a model based on Genetic Algorithms to obtain scenarios where free chlorine is maintained at the minimum permissible concentration throughout the day. In addition, Water Managers could optimize the use of disinfectant by implementing booster chlorination stations (BCSs). The results show that chlorine use could be reduced by 38%, therefore guaranteeing the chlorine concentration limits along the WDN.


Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 1999
Author(s):  
Malvin S. Marlim ◽  
Doosun Kang

Contamination in water distribution networks (WDNs) can occur at any time and location. One protection measure in WDNs is the placement of water quality sensors (WQSs) to detect contamination and provide information for locating the potential contamination source. The placement of WQSs in WDNs must be optimally planned. Therefore, a robust sensor-placement strategy (SPS) is vital. The SPS should have clear objectives regarding what needs to be achieved by the sensor configuration. Here, the objectives of the SPS were set to cover the contamination event stages of detection, consumption, and source localization. As contamination events occur in any form of intrusion, at any location and time, the objectives had to be tested against many possible scenarios, and they needed to reach a fair value considering all scenarios. In this study, the particle swarm optimization (PSO) algorithm was selected as the optimizer. The SPS was further reinforced using a databasing method to improve its computational efficiency. The performance of the proposed method was examined by comparing it with a benchmark SPS example and applying it to DMA-sized, real WDNs. The proposed optimization approach improved the overall fitness of the configuration by 23.1% and showed a stable placement behavior with the increase in sensors.


2018 ◽  
Vol 108 ◽  
pp. 152-162 ◽  
Author(s):  
Adrià Soldevila ◽  
Joaquim Blesa ◽  
Sebastian Tornil-Sin ◽  
Rosa M. Fernandez-Canti ◽  
Vicenç Puig

2017 ◽  
Vol 20 (6) ◽  
pp. 1286-1295 ◽  
Author(s):  
Xiang Xie ◽  
Quan Zhou ◽  
Dibo Hou ◽  
Hongjian Zhang

Abstract The performance of model-based leak detection and localization techniques heavily depends on the configuration of a limited number of sensors. This paper presents a sensor placement optimization strategy that guarantees sufficient diagnosability while satisfying the budget constraint. Based on the theory of compressed sensing, the leak localization problem could be transformed into acquiring the sparse leak-induced demands from the available measurements, and the average mutual coherence is devised as a diagnosability criterion for evaluating whether the measurements contain enough information for identifying the potential leaks. The optimal sensor placement problem is then reformulated as a {0, 1} quadratic knapsack problem, seeking an optimal sensor placement scheme by minimizing the average mutual coherence to maximize the degree of diagnosability. To effectively handle the complicated real-life water distribution networks, a validated binary version of artificial bee colony algorithm enhanced by genetic operators, including crossover and swap, is introduced to solve the binary knapsack problem. The proposed strategy is illustrated and validated through a real-life water distribution network with synthetically generated field data.


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