Water Distribution System Modeling and Remote Monitoring

2008 ◽  
Vol 38 ◽  
pp. 132-142 ◽  
Author(s):  
Vicki L. Van Blaricum ◽  
Vincent F. Hock
Keyword(s):  
Water Quality ◽  
Remote Monitoring ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
System Modeling ◽  
Hydraulic Simulation ◽  
Internal Corrosion ◽  
Water Quality Sensors ◽  
Fine Tune

Localized internal corrosion of water distribution piping is difficult to detect, diagnose, and mitigate. This paper describes the demonstration and validation of multi-parameter water quality sensors and corrosion rate sensors that were permanently installed at a U. S. Army installation to detect corrosion problems and fine-tune the chemical treatment program. This paper will include results of the sensor demonstration and validation. Follow-on work includes the integration of the sensors with a dynamic real-time water distribution system chemical and hydraulic simulation. This work will also be described.

scholarly journals Water Quality Monitoring Sensors Optimum Location in a Metropolitan Supply Network

2020 ◽  
Vol 71 (1) ◽  
pp. 327-334
Author(s):  
Albert Titus Constantin ◽  
Gheorghe I. Lazar ◽  
Serban-Vlad Nicoara
Keyword(s):  
Water Quality ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Supply Network ◽  
Optimum Location ◽  
Software Toolkit ◽  
Water Quality Sensors

The discrete numerical model developed by the help of TEVA-SPOT specialized software toolkit serves to a subsequent analysis that looks to estimate the water distribution system vulnerability in case of a contaminant agent release. The optimum location of the water quality sensors attached to a number of joints in the Timisoara (Romania) metropolitan water supply network can be reached in order to warn the company management and competent authorities and so to reduce the contamination effects upon the consumers.

Fuzzy Evaluation of Water Quality in Water Distribution System Based on Entropy Weight and EPANET

2012 ◽  
Vol 518-523 ◽  
pp. 3703-3706
Author(s):  
Ling Ping Zhao ◽  
Fen Ge Zhang ◽  
Liang Fei Dong ◽  
Yong Wei ◽  
Bao Hua Tu ◽  
...  
Keyword(s):  
Water Quality ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Evaluation Model ◽  
Fuzzy Evaluation ◽  
Entropy Weight ◽  
Simulation Data ◽  
Fuzzy Evaluation Model

According to the fuzziness of water quality in water distribution system, based on the simulation data of water quality obtained by using EPANET software,and applying entropy weight theory in the fuzzy evaluation of water quality, fuzzy evaluation model of water quality based on entropy weight and EPANET is established. Water quality in water distribution system of Hengshanqiao town is evaluated by using this method.Evaluation results are relatively objective and credible, proving that the method is simple and practical, scientific and reliable.

scholarly journals Prognosis of Water Quality Sensors Using Advanced Data Analytics: Application to the Barcelona Drinking Water Network

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1342 ◽  
Author(s):  
Diego Garcia ◽  
Vicenç Puig ◽  
Joseba Quevedo
Keyword(s):  
Water Quality ◽  
Distribution System ◽  
Data Analytics ◽  
Water Distribution ◽  
Discrete Event ◽  
Spatial Models ◽  
Remaining Useful Life ◽  
Health State ◽  
Using Data ◽  
Water Quality Sensors

Water Utilities (WU) are responsible for supplying water for residential, commercial and industrial use guaranteeing the sanitary and quality standards established by different regulations. To assure the satisfaction of such standards a set of quality sensors that monitor continuously the Water Distribution System (WDS) are used. Unfortunately, those sensors require continuous maintenance in order to guarantee their right and reliable operation. In order to program the maintenance of those sensors taking into account the health state of the sensor, a prognosis system should be deployed. Moreover, before proceeding with the prognosis of the sensors, the data provided with those sensors should be validated using data from other sensors and models. This paper provides an advanced data analytics framework that will allow us to diagnose water quality sensor faults and to detect water quality events. Moreover, a data-driven prognosis module will be able to assess the sensitivity degradation of the chlorine sensors estimating the remaining useful life (RUL), taking into account uncertainty quantification, that allows us to program the maintenance actions based on the state of health of sensors instead on a regular basis. The fault and event detection module is based on a methodology that combines time and spatial models obtained from historical data that are integrated with a discrete-event system and are able to distinguish between a quality event or a sensor fault. The prognosis module analyses the quality sensor time series forecasting the degradation and therefore providing a predictive maintenance plan avoiding unsafe situations in the WDS.

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