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Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi

Water distribution systems and their integrity are essential for human life and society. Maintaining them is very challenging and becomes the main issue for many developed and underdeveloped countries. Loss of water may happen in many different ways such as evaporation of free water surfaces, leakag...

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Main Author: Sherksi, Nasereddin Ibrahim
Format: Thesis
Language:English
Published: 2020
Subjects:
Neural networks (Computer science)
Algorithms
Online Access:https://ir.uitm.edu.my/id/eprint/61061/1/61061.pdf
https://ir.uitm.edu.my/id/eprint/61061/
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spelling my.uitm.ir.610612022-06-07T07:25:03Z https://ir.uitm.edu.my/id/eprint/61061/ Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi Sherksi, Nasereddin Ibrahim Neural networks (Computer science) Algorithms Water distribution systems and their integrity are essential for human life and society. Maintaining them is very challenging and becomes the main issue for many developed and underdeveloped countries. Loss of water may happen in many different ways such as evaporation of free water surfaces, leakage, inaccurate metering and unmetered usage. Water distribution systems contain pipes with different diameters, pumps, junction, valves and tanks to transport water through the system, and water leakage in the system represents a serious economic costs. All water distribution networks suffer from leaks and the amount of leakage widely varies between countries and regions within a country. This thesis proposes a classification model to detect water leakage, focusing on finding water leakage’s location and size, using K-Nearest Neighbour (K-NN) classification method. The system is simulated using EPANET (Environmental Prediction Agency Network) software based on actual water distribution system (WDS) data from Benghazi city, Libya. The data used in this thesis can be divided into two types. Firstly, data collected from available sources as Supervisory Control and Data Acquisition (SCADA). Secondly, the data collected from the main valve chamber controllers, which are located in the main pipes. The successfully achieved four set objectives inclusive of (1) a new classification model to detect water leakage, (2) analysis of the effects of leakage size on the variables within a WDS, i.e. flow, pressure, pipe volume, velocity and water demand, (3) locating and specifying the leakage size in the WDS, and (4) evaluate the performance of the designed K-NN algorithm for accurate leak detection. The study showed that the best model of the K-NN technique produces a classification accuracy is 100% for the leak size and 96.5 % for the leak location. 2020-04 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/61061/1/61061.pdf Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi. (2020) PhD thesis, thesis, Universiti Teknologi MARA.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Neural networks (Computer science)
Algorithms
spellingShingle Neural networks (Computer science)
Algorithms
Sherksi, Nasereddin Ibrahim
Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi
description Water distribution systems and their integrity are essential for human life and society. Maintaining them is very challenging and becomes the main issue for many developed and underdeveloped countries. Loss of water may happen in many different ways such as evaporation of free water surfaces, leakage, inaccurate metering and unmetered usage. Water distribution systems contain pipes with different diameters, pumps, junction, valves and tanks to transport water through the system, and water leakage in the system represents a serious economic costs. All water distribution networks suffer from leaks and the amount of leakage widely varies between countries and regions within a country. This thesis proposes a classification model to detect water leakage, focusing on finding water leakage’s location and size, using K-Nearest Neighbour (K-NN) classification method. The system is simulated using EPANET (Environmental Prediction Agency Network) software based on actual water distribution system (WDS) data from Benghazi city, Libya. The data used in this thesis can be divided into two types. Firstly, data collected from available sources as Supervisory Control and Data Acquisition (SCADA). Secondly, the data collected from the main valve chamber controllers, which are located in the main pipes. The successfully achieved four set objectives inclusive of (1) a new classification model to detect water leakage, (2) analysis of the effects of leakage size on the variables within a WDS, i.e. flow, pressure, pipe volume, velocity and water demand, (3) locating and specifying the leakage size in the WDS, and (4) evaluate the performance of the designed K-NN algorithm for accurate leak detection. The study showed that the best model of the K-NN technique produces a classification accuracy is 100% for the leak size and 96.5 % for the leak location.
format Thesis
author Sherksi, Nasereddin Ibrahim
author_facet Sherksi, Nasereddin Ibrahim
author_sort Sherksi, Nasereddin Ibrahim
title Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi
title_short Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi
title_full Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi
title_fullStr Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi
title_full_unstemmed Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi
title_sort detection of leak size and its location in a water distribution system by using k-nn / nasereddin ibrahim sherksi
publishDate 2020
url https://ir.uitm.edu.my/id/eprint/61061/1/61061.pdf
https://ir.uitm.edu.my/id/eprint/61061/
_version_ 1735389680027828224
score 13.211869

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