Methodological Approach for the Rehabilitation of Water Distribution Systems: Case Study Application Based on the CARE-W System

2008 ◽  
Author(s):  
Helena Alegre ◽  
Julieta Marques ◽  
André Pina ◽  
Sofia Coelho
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Methodological Approach ◽  
Water Distribution Systems ◽  
Study Application

Detecting Cyber-Physical Attacks in Water Distribution Systems: One-class Classifier Approach

2020 ◽  
Author(s):  
Mashor Housh ◽  
Noy Kadosh ◽  
Alex Frid
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Attack Detection ◽  
Support Vector ◽  
Features Selection ◽  
Cyber Attack ◽  
Detection Problem ◽  
One Class Classification

<p>Water Distribution Systems (WDSs) are critical infrastructures that supply drinking water from water sources to end-users. Smart WDSs could be designed by integrating physical components (e.g. valve and pumps) with computation and networking devices. As such, in smart WDSs, pumps and valves are automatically controlled together with continuous monitoring of important systems' parameters. However, despite its advantage of improved efficacy, the automated control and operation through a cyber-layer can expose the system to cyber-physical attacks. One-Class classification technique is proposed to detect such attacks by analyzing collected sensors' readings from the system components. One-class classifiers have been found suitable for classifying "normal" and "abnormal" conditions with unbalanced datasets, which are expected in the cyber-attack detection problem. In the cyber-attack detection problem, typically, most of the data samples are under the "normal" state, and only small fraction of the samples can be suspected as under-attack (i.e. "abnormal" state). The results of this study demonstrate that one-class classification algorithms can be suitable for the cyber-attack detection problem and can compete with existing approaches. More specifically, this study examines the Support Vector Data Description (SVDD) method together with a tailored features selection methodology, which is based on the physical understanding of the WDS topology. The developed algorithm is examined on BATADAL datasets, which demonstrate a quasi-realistic case study and on a new case study of a large-scale WDS.</p>

scholarly journals Optimal selection of number and location of pressure sensors in water distribution systems using geostatistical tools coupled with genetic algorithm

2019 ◽  
Vol 21 (6) ◽  
pp. 1030-1047 ◽  
Author(s):  
Fattah Soroush ◽  
Mohammad J. Abedini
Keyword(s):  
Genetic Algorithm ◽  
Distribution Systems ◽  
Water Distribution ◽  
Random Search ◽  
Water Distribution Systems ◽  
Pressure Sensors ◽  
Monitoring Network ◽  
Search Optimization ◽  
First Time

Abstract This paper presents a novel methodology for designing an optimal pressure sensor to make average pressure field in water distribution systems (WDS) more accurate via geostatistical tools coupled with genetic algorithm (GA) under normal operating condition. In light of this, the objective function is introduced based on geostatistical technique as variance of residual of block ordinary kriging (BOK). In order to solve the problem of sensor placement, three different approaches, so-called, simplified, exhaustive, and random search optimization are considered. To the best of the authors' knowledge, this is the first time whereby geostatistical tools are used to design a pressure monitoring network in the WDS. The proposed methodology is first tested and verified on a literature case study of Anytown WDS and then is applied to a real-world case study referred to as C-Town consisting of five district metered areas (DMAs). The proposed methodology has several advantages over existing more conventional approaches which will be demonstrated in this paper. The results indicate that this method outperforms the conventional paradigms in current use in terms of mathematical labor and the results are quite promising.

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