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.

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.

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.

Dynamic updating of post-earthquake damage and functional restoration forecasts of water distribution systems using Bayesian inferencing

2021 ◽  
pp. 875529302110380
Author(s):  
Agam Tomar ◽  
Henry V Burton ◽  
Ali Mosleh
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Epistemic Uncertainty ◽  
Discrete Event ◽  
Complete Recovery ◽  
Current Data ◽  
Functional Restoration ◽  
Mitigation Measures ◽  
Total Recovery

A framework for dynamically updating post-earthquake functional recovery forecasts is presented to reduce the epistemic uncertainty in the predictive model. A Bayesian Network (BN) model is used to provide estimates of the total recovery time, and a process-based discrete event simulation (PBDES) model generates forecasts of the complete recovery trajectory. Both models rely on component damage and duration-based input parameters that are dynamically updated using Bayes’ theorem, as information becomes available throughout the recovery process. The effectiveness of the proposed framework is demonstrated through an application to the pipe network of the City of Napa water distribution system. More specifically, pipe damage and repair data from the 2014 earthquake are used as a point of comparison for the dynamic forecasts. It is shown that, over time, the mean value of the total recovery duration generated by the BN-based model converges to the observed value and the dispersion is reduced. Also, despite a crude initial estimate, the median trajectory generated by the PBDES model provides a reasonable approximation of the observed recovery within 30 days following the earthquake. The proposed framework can be used by emergency managers to investigate the efficacy of post-event mitigation measures (e.g. crew allocation, resource prioritization) utilizing the most current data and knowledge.

scholarly journals Certainty Level of Water Delivery of the Required Quality by Water Supply Networks

2019 ◽  
Vol 16 (10) ◽  
pp. 1860 ◽  
Author(s):  
Marian Kwietniewski ◽  
Katarzyna Miszta-Kruk ◽  
Kaja Niewitecka ◽  
Mirosław Sudoł ◽  
Krzysztof Gaska
Keyword(s):  
Water Quality ◽  
Water Supply ◽  
Quality Indicators ◽  
Distribution System ◽  
Water Distribution ◽  
Water Delivery ◽  
Supply Networks ◽  
Water Quality Indicators ◽  
Water Supply Networks ◽  
Required Quality

The security of water delivery of the required quality by water supply networks is identified with the concept of reliability. Therefore, a method of reliability evaluation of water distribution of the required quality was developed. The method is based on the probabilistic character of secondary water contamination in the water supply network. Data for the method are taken from monitoring of the water distribution system. The method takes into consideration the number and locations of individual measurement points and the results of the tests of water quality indicators at these points. The sets of measurement points and water quality indicators constitute a matrix research (observation) field in the model. The proposed method was implemented to assess the reliability of a water distribution process with respect to water with the required microbiological quality indicators in a real distribution system.

scholarly journals Water quality event detection and customer complaint clustering analysis in distribution systems

2012 ◽  
Vol 12 (5) ◽  
pp. 580-587 ◽  
Author(s):  
Stephen Mounce ◽  
John Machell ◽  
Joby Boxall
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Source ◽  
Water Quality Monitoring ◽  
Water Utility ◽  
Drinking Water Distribution ◽  
Historic Data

Safe, clean drinking water is a foundation of society and water quality monitoring can contribute to ensuring this. A case study application of the CANARY software to historic data from a UK drinking water distribution system is described. Sensitivity studies explored appropriate choice of algorithmic parameter settings for a baseline site, performance was evaluated with artificial events and the system then transferred to all sites. Results are presented for analysis of nine water quality sensors measuring six parameters and deployed in three connected district meter areas (DMAs), fed from a single water source (service reservoir), for a 1 year period and evaluated using comprehensive water utility records with 86% of event clusters successfully correlated to causes (spatially limited to DMA level). False negatives, defined by temporal clusters of water quality complaints in the pilot area not corresponding to detections, were only approximately 25%. It was demonstrated that the software could be configured and applied retrospectively (with potential for future near real time application) to detect various water quality event types (with a wider remit than contamination alone) for further interpretation.

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