Leak detection in medium density polyethylene pipe using ensemble empirical mode decomposition method

Nowadays, there are many approaches to the methods for detecting pipeline’s feature either from external or internal. The only argument is which method will deliver the most effective result with the advantage of time-saving and human-friendly. The results were influenced by the surrounding noise ei...

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Main Author: Makeen, Mohd Amin
Format: Thesis
Language:English
Published: 2018
Online Access:http://umpir.ump.edu.my/id/eprint/33612/1/Leak%20detection%20in%20medium%20density%20polyethylene%20pipe%20using%20ensemble.wm.pdf
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author Makeen, Mohd Amin
author_facet Makeen, Mohd Amin
author_sort Makeen, Mohd Amin
collection UMP
description Nowadays, there are many approaches to the methods for detecting pipeline’s feature either from external or internal. The only argument is which method will deliver the most effective result with the advantage of time-saving and human-friendly. The results were influenced by the surrounding noise either from inner or the outer pipeline networks. This thesis mainly focuses on the detection features in pipeline network using Ensemble Empirical Mode Decomposition Method (EEMD). The objectives of this thesis are to study and analyse data by using EEMD method for leakage detection in the pipeline system and identify and compare the leakage position between the measured distance and analysed distance. Therefore, the test rig was built by using 56m polyethene pipe with the leak as the main feature. Solenoid valve is used to create water hammering phenomenon. The water hammering phenomenon will generate a transient wave inside the pipe. The data was collected using DASYLab software and analysed using MATLAB software. The leakage and outlet position were determined by undergoing intrinsic mode function analysis (IMF) and later analysed by their respective instantaneous frequency analysis (IF) using EEMD method. The experiment was runs in two situations, firstly by closing the leakage valve and the other one by opening the valve to create leakage. The analysed results show that the position of the outlet is almost similar to the measured distance with 0.55% and 6% of percentage error. The analysed leakage location is also determined and compared to the measured distance. It indicates that only 3.21% of error between the measured distance and analysed distance and analysed distance. It can be concluded that the EEMD analysis is one of the best methods to be the approach in leak detection of either underground or above ground piping system. In addition, this method can be said as low in cost and energy saving.
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spelling UMPir336122023-03-15T03:32:18Z http://umpir.ump.edu.my/id/eprint/33612/ Leak detection in medium density polyethylene pipe using ensemble empirical mode decomposition method Makeen, Mohd Amin Nowadays, there are many approaches to the methods for detecting pipeline’s feature either from external or internal. The only argument is which method will deliver the most effective result with the advantage of time-saving and human-friendly. The results were influenced by the surrounding noise either from inner or the outer pipeline networks. This thesis mainly focuses on the detection features in pipeline network using Ensemble Empirical Mode Decomposition Method (EEMD). The objectives of this thesis are to study and analyse data by using EEMD method for leakage detection in the pipeline system and identify and compare the leakage position between the measured distance and analysed distance. Therefore, the test rig was built by using 56m polyethene pipe with the leak as the main feature. Solenoid valve is used to create water hammering phenomenon. The water hammering phenomenon will generate a transient wave inside the pipe. The data was collected using DASYLab software and analysed using MATLAB software. The leakage and outlet position were determined by undergoing intrinsic mode function analysis (IMF) and later analysed by their respective instantaneous frequency analysis (IF) using EEMD method. The experiment was runs in two situations, firstly by closing the leakage valve and the other one by opening the valve to create leakage. The analysed results show that the position of the outlet is almost similar to the measured distance with 0.55% and 6% of percentage error. The analysed leakage location is also determined and compared to the measured distance. It indicates that only 3.21% of error between the measured distance and analysed distance and analysed distance. It can be concluded that the EEMD analysis is one of the best methods to be the approach in leak detection of either underground or above ground piping system. In addition, this method can be said as low in cost and energy saving. 2018-07 Thesis NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/33612/1/Leak%20detection%20in%20medium%20density%20polyethylene%20pipe%20using%20ensemble.wm.pdf Makeen, Mohd Amin (2018) Leak detection in medium density polyethylene pipe using ensemble empirical mode decomposition method. Masters thesis, Universiti Malaysia Pahang (Contributors, Thesis advisor: Mohd. Fairusham, Ghazali).
spellingShingle Makeen, Mohd Amin
Leak detection in medium density polyethylene pipe using ensemble empirical mode decomposition method
title Leak detection in medium density polyethylene pipe using ensemble empirical mode decomposition method
title_full Leak detection in medium density polyethylene pipe using ensemble empirical mode decomposition method
title_fullStr Leak detection in medium density polyethylene pipe using ensemble empirical mode decomposition method
title_full_unstemmed Leak detection in medium density polyethylene pipe using ensemble empirical mode decomposition method
title_short Leak detection in medium density polyethylene pipe using ensemble empirical mode decomposition method
title_sort leak detection in medium density polyethylene pipe using ensemble empirical mode decomposition method
url http://umpir.ump.edu.my/id/eprint/33612/1/Leak%20detection%20in%20medium%20density%20polyethylene%20pipe%20using%20ensemble.wm.pdf
work_keys_str_mv AT makeenmohdamin leakdetectioninmediumdensitypolyethylenepipeusingensembleempiricalmodedecompositionmethod