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
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id	my-uitm-ir.61061
record_format	uketd_dc
spelling	my-uitm-ir.610612022-06-07T07:25:03Z Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi 2020-04 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 https://ir.uitm.edu.my/id/eprint/61061/ https://ir.uitm.edu.my/id/eprint/61061/1/61061.pdf text en public phd doctoral Universiti Teknologi MARA Faculty of Electrical Engineering Taib, Mohd Nasir (Prof. Ir. Ts. Dr.)
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Taib, Mohd Nasir (Prof. Ir. Ts. Dr.)
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
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
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
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Electrical Engineering
publishDate	2020
url	https://ir.uitm.edu.my/id/eprint/61061/1/61061.pdf
_version_	1783735205782093824

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

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