Transient-based leak detection and monitoring of water pipes using complementary ensemble empirical mode decomposition (CEEMD) method
Transient signal occurs when there is sudden change of pressure inside the pipeline especially due to pressure surge or opening and closing valve. Decomposition method applied in this study to analyze the transient signal and remove noise that contaminate the signal. In this paper, an adaptive decom...
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Akademi Baru
2021
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Online Access: | http://umpir.ump.edu.my/id/eprint/31931/1/Transient-based%20leak%20detection%20and%20monitoring%20of%20water.pdf http://umpir.ump.edu.my/id/eprint/31931/ https://doi.org/10.37934/arfmts.83.2.135148 https://doi.org/10.37934/arfmts.83.2.135148 |
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my.ump.umpir.319312021-09-07T04:39:53Z http://umpir.ump.edu.my/id/eprint/31931/ Transient-based leak detection and monitoring of water pipes using complementary ensemble empirical mode decomposition (CEEMD) method Muhammad Aminuddin, Pi Remli M. F., Ghazali Azmi, W. H. Hanafi, M. Yusop TJ Mechanical engineering and machinery TL Motor vehicles. Aeronautics. Astronautics Transient signal occurs when there is sudden change of pressure inside the pipeline especially due to pressure surge or opening and closing valve. Decomposition method applied in this study to analyze the transient signal and remove noise that contaminate the signal. In this paper, an adaptive decomposition algorithm that is Complementary Ensemble Empirical Mode Decomposition (CEEMD) proposed in order to overcome the problem occur in Hilbert-Huang Transform (HHT) method. This method takes over the Empirical Mode Decomposition (EMD) method that purpose as pre-processing method in HHT. This improvement made to overcome mode mixing and reconstruction error that lies in EMD method. CEEMD method used to extract the IMF’s component of a contaminated signal to remove undesirable noise signal. Instantaneous analysis using Hilbert Transform (HT) apply for selected IMF to locate the feature’s position along the pipeline. The result prove that proposed decomposition method show success with the percentage of error between measured and analysed distance only below that 4% for all features extracted. Akademi Baru 2021-06-17 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/31931/1/Transient-based%20leak%20detection%20and%20monitoring%20of%20water.pdf Muhammad Aminuddin, Pi Remli and M. F., Ghazali and Azmi, W. H. and Hanafi, M. Yusop (2021) Transient-based leak detection and monitoring of water pipes using complementary ensemble empirical mode decomposition (CEEMD) method. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences, 83 (2). pp. 135-148. ISSN 2289-7879 https://doi.org/10.37934/arfmts.83.2.135148 https://doi.org/10.37934/arfmts.83.2.135148 |
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TJ Mechanical engineering and machinery TL Motor vehicles. Aeronautics. Astronautics Muhammad Aminuddin, Pi Remli M. F., Ghazali Azmi, W. H. Hanafi, M. Yusop Transient-based leak detection and monitoring of water pipes using complementary ensemble empirical mode decomposition (CEEMD) method |
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Transient signal occurs when there is sudden change of pressure inside the pipeline especially due to pressure surge or opening and closing valve. Decomposition method applied in this study to analyze the transient signal and remove noise that contaminate the signal. In this paper, an adaptive decomposition algorithm that is Complementary Ensemble Empirical Mode Decomposition (CEEMD) proposed in order to overcome the problem occur in Hilbert-Huang Transform (HHT) method. This method takes over the Empirical Mode Decomposition (EMD) method that purpose as pre-processing method in HHT. This improvement made to overcome mode mixing and reconstruction error that lies in EMD method. CEEMD method used to extract the IMF’s component of a contaminated signal to remove undesirable noise signal. Instantaneous analysis using Hilbert Transform (HT) apply for selected IMF to locate the feature’s position along the pipeline. The result prove that proposed decomposition method show success with the percentage of error between measured and analysed distance only below that 4% for all features extracted. |
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Article |
author |
Muhammad Aminuddin, Pi Remli M. F., Ghazali Azmi, W. H. Hanafi, M. Yusop |
author_facet |
Muhammad Aminuddin, Pi Remli M. F., Ghazali Azmi, W. H. Hanafi, M. Yusop |
author_sort |
Muhammad Aminuddin, Pi Remli |
title |
Transient-based leak detection and monitoring of water pipes using complementary ensemble empirical mode decomposition (CEEMD) method |
title_short |
Transient-based leak detection and monitoring of water pipes using complementary ensemble empirical mode decomposition (CEEMD) method |
title_full |
Transient-based leak detection and monitoring of water pipes using complementary ensemble empirical mode decomposition (CEEMD) method |
title_fullStr |
Transient-based leak detection and monitoring of water pipes using complementary ensemble empirical mode decomposition (CEEMD) method |
title_full_unstemmed |
Transient-based leak detection and monitoring of water pipes using complementary ensemble empirical mode decomposition (CEEMD) method |
title_sort |
transient-based leak detection and monitoring of water pipes using complementary ensemble empirical mode decomposition (ceemd) method |
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Akademi Baru |
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2021 |
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http://umpir.ump.edu.my/id/eprint/31931/1/Transient-based%20leak%20detection%20and%20monitoring%20of%20water.pdf http://umpir.ump.edu.my/id/eprint/31931/ https://doi.org/10.37934/arfmts.83.2.135148 https://doi.org/10.37934/arfmts.83.2.135148 |
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