Pipeline fault identification using synchrosqueezed wavelet transform based on pressure transient analysis
Brand modern technology of leak detection by using pressure transient analysis has been developed and interested to research due to its advantages such as low cost, simplicity and convenient to use. This technology uses the concept of signal reflections which identify pipeline features. The method u...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Semarak Ilmu Publishing
2022
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/36603/1/Pipeline%20Fault%20Identification%20using%20Synchrosqueezed%20Wavelet%20Transform.pdf |
| _version_ | 1796995526539870208 |
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| author | Pi Remli, M. A. Ghazali, M. F. Yusof, M. F.M. Yusop, Muhammad Hanafi Wai, Sit Kian Sidek, Sufian Najafi, G. |
| author_facet | Pi Remli, M. A. Ghazali, M. F. Yusof, M. F.M. Yusop, Muhammad Hanafi Wai, Sit Kian Sidek, Sufian Najafi, G. |
| author_sort | Pi Remli, M. A. |
| collection | UMP |
| description | Brand modern technology of leak detection by using pressure transient analysis has been developed and interested to research due to its advantages such as low cost, simplicity and convenient to use. This technology uses the concept of signal reflections which identify pipeline features. The method used in this study was using a pressure transducer (piezoelectric pressure sensor) to obtain pressure transient respond generated by rapid opening and closing of solenoid valve. However, such reflections are very difficult to determine the pipe characteristic most probably because of excessive noise from other sources. Therefore, this paper proposed a method called Empirical Mode Decomposition (EMD) to decompose the reflection signal to its Intrinsic Mode Function (IMFs) and further analysis using continuous wavelet transform (CWT) to transform the signal into Time-Frequency domain and spectrum diagram. From the spectrum diagram, the characteristic of the pipe can be clearly display. From the finding results, it proves that this method not only useful for leak detection but also can determine the location of leak and its magnitude with error less than 10%. |
| first_indexed | 2024-03-06T13:03:39Z |
| format | Article |
| id | UMPir36603 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T13:03:39Z |
| publishDate | 2022 |
| publisher | Semarak Ilmu Publishing |
| record_format | dspace |
| spelling | UMPir366032023-01-05T00:45:11Z http://umpir.ump.edu.my/id/eprint/36603/ Pipeline fault identification using synchrosqueezed wavelet transform based on pressure transient analysis Pi Remli, M. A. Ghazali, M. F. Yusof, M. F.M. Yusop, Muhammad Hanafi Wai, Sit Kian Sidek, Sufian Najafi, G. TJ Mechanical engineering and machinery TL Motor vehicles. Aeronautics. Astronautics Brand modern technology of leak detection by using pressure transient analysis has been developed and interested to research due to its advantages such as low cost, simplicity and convenient to use. This technology uses the concept of signal reflections which identify pipeline features. The method used in this study was using a pressure transducer (piezoelectric pressure sensor) to obtain pressure transient respond generated by rapid opening and closing of solenoid valve. However, such reflections are very difficult to determine the pipe characteristic most probably because of excessive noise from other sources. Therefore, this paper proposed a method called Empirical Mode Decomposition (EMD) to decompose the reflection signal to its Intrinsic Mode Function (IMFs) and further analysis using continuous wavelet transform (CWT) to transform the signal into Time-Frequency domain and spectrum diagram. From the spectrum diagram, the characteristic of the pipe can be clearly display. From the finding results, it proves that this method not only useful for leak detection but also can determine the location of leak and its magnitude with error less than 10%. Semarak Ilmu Publishing 2022-06 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/36603/1/Pipeline%20Fault%20Identification%20using%20Synchrosqueezed%20Wavelet%20Transform.pdf Pi Remli, M. A. and Ghazali, M. F. and Yusof, M. F.M. and Yusop, Muhammad Hanafi and Wai, Sit Kian and Sidek, Sufian and Najafi, G. (2022) Pipeline fault identification using synchrosqueezed wavelet transform based on pressure transient analysis. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences, 96 (2). pp. 158-171. ISSN 2289 - 7879. (Published) https://doi.org/10.37934/arfmts.96.2.158171 https://doi.org/10.37934/arfmts.96.2.158171 |
| spellingShingle | TJ Mechanical engineering and machinery TL Motor vehicles. Aeronautics. Astronautics Pi Remli, M. A. Ghazali, M. F. Yusof, M. F.M. Yusop, Muhammad Hanafi Wai, Sit Kian Sidek, Sufian Najafi, G. Pipeline fault identification using synchrosqueezed wavelet transform based on pressure transient analysis |
| title | Pipeline fault identification using synchrosqueezed wavelet transform based on pressure transient analysis |
| title_full | Pipeline fault identification using synchrosqueezed wavelet transform based on pressure transient analysis |
| title_fullStr | Pipeline fault identification using synchrosqueezed wavelet transform based on pressure transient analysis |
| title_full_unstemmed | Pipeline fault identification using synchrosqueezed wavelet transform based on pressure transient analysis |
| title_short | Pipeline fault identification using synchrosqueezed wavelet transform based on pressure transient analysis |
| title_sort | pipeline fault identification using synchrosqueezed wavelet transform based on pressure transient analysis |
| topic | TJ Mechanical engineering and machinery TL Motor vehicles. Aeronautics. Astronautics |
| url | http://umpir.ump.edu.my/id/eprint/36603/1/Pipeline%20Fault%20Identification%20using%20Synchrosqueezed%20Wavelet%20Transform.pdf |
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