Leakage detection in Tsumeb east water distribution network using EPANET and support vector regression

Kemba, Joseph; Gideon, Kenneth; Nyirenda, Clement N.

doi:10.23919/istafrica.2017.8102401

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…Softwares like EPANET, commercial hydraulic simulators are used for building pipeline systems. EPANET ( 57) is a software that is specially used for simulation of water distribution networks (58), as shown in figure 5 Modeling. Once the data collection is done, it is passed into a neural network trained for classification.…”

Section: Methodology For Developing a Leak Detection System Using Annmentioning

confidence: 99%

Studies on Leak Detection in Process Pipelines Using Artificial Neural Networks/Machine Learning

Meda¹,

Harshitha²,

`Hulake³

et al. 2022

ECS Trans.

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In process industries, leakage in pipelines is common and an environmental, health and economic issue to be addressed without fail. To detect the presence of leaks in pipelines, there are several conventional leak detection techniques that are available. From the literature, conventional leak detection techniques can be mainly classified into: hardware-based, visual and software-based methods. Researchers have focused more on software-based methods due to simple and reliable operation. Under software-based methods, using machine learning algorithms that is a data driven approach for leak detection and localization is becoming popular because of learning capabilities. Therefore, in this review, several recent conventional leak detection methods and artificial neural networks/machine learning based leak detection methods are described. It is an attempt made to identify leak detection techniques along with the common methodology followed for building a leak detection system using artificial neural networks/machine learning.

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Section: Methodology For Developing a Leak Detection System Using Annmentioning

confidence: 99%

Studies on Leak Detection in Process Pipelines Using Artificial Neural Networks/Machine Learning

Meda¹,

Harshitha²,

`Hulake³

et al. 2022

ECS Trans.

View full text Add to dashboard Cite

show abstract

“…Node labels were mapped to actual distance and accuracy was calculated by dividing all predictionswith sample and multiplying result by one hundred. Correlation coefficient and RMSE for each set was also calculated [2]. EPANET can be used in different modes and it drives from Water Net Gen that completely describesleakage detection in links [3].…”

Section: Literature Reviewmentioning

confidence: 99%

Leakage Detection through HL in Gurthali Water Supply Distribution Network using EPANET

Neeraj*,

Nawal,

Bundele

et al. 2020

IJITEE

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Water distribution network (WDN) design of hydraulic model Gurthali, NARWANA-JIND, HARYANA and objective of this paper to detecting the leakage in it.In current research work to find out the Hl through normal valve and leak valve control setting with randomly value.To detect the Head Loss to usedDarcy Weisbach methodwhich calculate the major and minor loss with friction in pipes links. EPANET tool is used to create enlarge hydraulic model and simulate the data. All the pipes to be analysis unit head loss and nodes analysis head loss foe every houses. For leak detection, four normal valve include to compute head loss or pressure drop on nodes, pipes and leak detection valves. Also find out the pressure and head loss on the all nodes and pipes.MS Excel used for leak detection data, at the various head loss values in valves, nodes, pipes links. Plot the various graphs with head loss on valves which generated that HL reduces drastically

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Leak Detection in Smart Water Grids Using EPANET and Machine Learning Techniques

Nagaraj

Kotamreddy

Choudhary

et al. 2021

IETE Journal of Education

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Leakage detection in Tsumeb east water distribution network using EPANET and support vector regression

Cited by 6 publications

References 9 publications

Studies on Leak Detection in Process Pipelines Using Artificial Neural Networks/Machine Learning

Studies on Leak Detection in Process Pipelines Using Artificial Neural Networks/Machine Learning

Leakage Detection through HL in Gurthali Water Supply Distribution Network using EPANET

Leak Detection in Smart Water Grids Using EPANET and Machine Learning Techniques

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