id ump-23379
recordtype eprints
spelling ump-233792018-12-31T04:15:46Z http://umpir.ump.edu.my/id/eprint/23379/ Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique Muhammad Hanafi, Yusop TJ Mechanical engineering and machinery Signal processing is an important tool to analyse non-stationary and non linear data. Many techniques of analysis are available to process non stationary and non-linear data such as FFT, wavelets transform, and demodulation analysis. In a recent study, the analysis of pressure transient signals could be seen as an accurate and low-cost method for leak and feature detection in water distribution systems. Transient phenomena has occur due to the sudden changes in the fluid’s propagation in pipelines system caused by the rapid pressure and flow fluctuation. This is due to events such as closing and opening valves rapidly or through pump failure. Various methods of pressure transient analysis have been applied by several groups of researchers, such as cepstrum analysis, cross-correlation, wavelets analysis, empirical mode decomposition (EMD) and instantaneous frequency analysis. In this research, it is to apply the Hilbert-Huang transform (HHT) as a method to analyse the pressure transient signal. The HHT is a way to decompose a signal into intrinsic mode functions (IMF). However, this method has the difficulty in selecting the suitable IMF for the next data post-processing method, which is Hilbert Transform (HT). Previous researchers normally select the IMF visually, based on the user’s experience, and introduced a merit index that allows the automatic selection of the IMF. The current research presents the implementation of an integrated kurtosisbased algorithm for a z-filter technique (Ikaz) to kurtosis ratio (Ikaz-kurtosis), for this allows automatic selection of the IMF that should be used. This technique is demonstrated on a 67.90-meter medium high-density polyethylene (MDPE) pipe installed with a single artificial leak demonstrator. The results using the Ikaz-kurtosis ratio revealed that the method could be used as an automatic selection of the IMF even though the noise level ratio of the signal is lower. Despite this, the Ikaz-kurtosis ratio method is recommended as a means to implement an automatic selection technique of the IMF for HHT analysis. 2018-02 Thesis NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/23379/1/Transient%20analysis%20for%20leak%20signature%20identification%20based%20on%20Hilbert%20Huang%20transform%20and%20integrated%20kurtosis%20algorithm%20for%20z-notch%20filter%20technique%20-%20Table%20of%20contents.pdf pdf en http://umpir.ump.edu.my/id/eprint/23379/2/Transient%20analysis%20for%20leak%20signature%20identification%20based%20on%20Hilbert%20Huang%20transform%20and%20integrated%20kurtosis%20algorithm%20for%20z-notch%20filter%20technique%20-%20Abstract.pdf pdf en http://umpir.ump.edu.my/id/eprint/23379/3/Transient%20analysis%20for%20leak%20signature%20identification%20based%20on%20Hilbert%20Huang%20transform%20and%20integrated%20kurtosis%20algorithm%20for%20z-notch%20filter%20technique%20-%20References.pdf Muhammad Hanafi, Yusop (2018) Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique. Masters thesis, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:104435&theme=UMP2
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
English
English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Muhammad Hanafi, Yusop
Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique
description Signal processing is an important tool to analyse non-stationary and non linear data. Many techniques of analysis are available to process non stationary and non-linear data such as FFT, wavelets transform, and demodulation analysis. In a recent study, the analysis of pressure transient signals could be seen as an accurate and low-cost method for leak and feature detection in water distribution systems. Transient phenomena has occur due to the sudden changes in the fluid’s propagation in pipelines system caused by the rapid pressure and flow fluctuation. This is due to events such as closing and opening valves rapidly or through pump failure. Various methods of pressure transient analysis have been applied by several groups of researchers, such as cepstrum analysis, cross-correlation, wavelets analysis, empirical mode decomposition (EMD) and instantaneous frequency analysis. In this research, it is to apply the Hilbert-Huang transform (HHT) as a method to analyse the pressure transient signal. The HHT is a way to decompose a signal into intrinsic mode functions (IMF). However, this method has the difficulty in selecting the suitable IMF for the next data post-processing method, which is Hilbert Transform (HT). Previous researchers normally select the IMF visually, based on the user’s experience, and introduced a merit index that allows the automatic selection of the IMF. The current research presents the implementation of an integrated kurtosisbased algorithm for a z-filter technique (Ikaz) to kurtosis ratio (Ikaz-kurtosis), for this allows automatic selection of the IMF that should be used. This technique is demonstrated on a 67.90-meter medium high-density polyethylene (MDPE) pipe installed with a single artificial leak demonstrator. The results using the Ikaz-kurtosis ratio revealed that the method could be used as an automatic selection of the IMF even though the noise level ratio of the signal is lower. Despite this, the Ikaz-kurtosis ratio method is recommended as a means to implement an automatic selection technique of the IMF for HHT analysis.
format Thesis
author Muhammad Hanafi, Yusop
author_facet Muhammad Hanafi, Yusop
author_sort Muhammad Hanafi, Yusop
title Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique
title_short Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique
title_full Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique
title_fullStr Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique
title_full_unstemmed Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique
title_sort transient analysis for leak signature identification based on hilbert huang transform and integrated kurtosis algorithm for z-notch filter technique
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/23379/
http://umpir.ump.edu.my/id/eprint/23379/
http://umpir.ump.edu.my/id/eprint/23379/1/Transient%20analysis%20for%20leak%20signature%20identification%20based%20on%20Hilbert%20Huang%20transform%20and%20integrated%20kurtosis%20algorithm%20for%20z-notch%20filter%20technique%20-%20Table%20of%20contents.pdf
http://umpir.ump.edu.my/id/eprint/23379/2/Transient%20analysis%20for%20leak%20signature%20identification%20based%20on%20Hilbert%20Huang%20transform%20and%20integrated%20kurtosis%20algorithm%20for%20z-notch%20filter%20technique%20-%20Abstract.pdf
http://umpir.ump.edu.my/id/eprint/23379/3/Transient%20analysis%20for%20leak%20signature%20identification%20based%20on%20Hilbert%20Huang%20transform%20and%20integrated%20kurtosis%20algorithm%20for%20z-notch%20filter%20technique%20-%20References.pdf
first_indexed 2023-09-18T22:34:57Z
last_indexed 2023-09-18T22:34:57Z
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