UMP Institutional Repository

Detecting Leak in Gas Pipeline using Continuous Wavelet Transform and Kurtosis

N. F., Adnan and M. F., Ghazali (2015) Detecting Leak in Gas Pipeline using Continuous Wavelet Transform and Kurtosis. In: Proceeding Book Mucet 2014 : Engineering & Technology. Universiti Teknikal Malaysia Melaka (UTeM), Melaka, pp. 347-351. ISBN 978-967-0257-53-2

[img] PDF
Detecting_Leak_in_Gas_Pipeline_using_Continuous_Wavelet_Transform_and_Kurtosis.pdf - Published Version
Restricted to Repository staff only

Download (802kB) | Request a copy


The detection of the leak detection is the main investigation issue in order to get the fast and reliable leak detection method. Even thought the reasons for these leaks are very well known, some of the current method is quite complicated and not precise. In addition, it is all about time consuming and cost of instalment. In this paper, we proposed a leak detection method using acoustic. The chirp signal injected into the pipeline system and the estimation of the leak detection from the delay time passing by the reflection of pressure wave in the pipeline if there have a leak. Using wavelet as the noise filtering, there can give a useful signal to verify the leak. Wavelet is the tool to de-noise the noise from the original signal and then tuned using maximum values of kurtosis. The main idea is the echoes detection of the pressure wave from the signal given by the original signal. Kurtosis plays the main role as the component to choose the filter parameter because of their nature to measure spikiness. The result shows that the highest value of kurtosis for the pipeline with leak is 6.465 while for the pipe without leak, the highest value for the kurtosis 5.3214.

Item Type: Book Section
Additional Information: 8th Malaysian Technical Universities Conference on Engineering & Technology (MUCET 2014), 10-11 November 2014, Mahkota Hotel Bandar Hilir Melaka
Uncontrolled Keywords: leak detection, gas pipeline, wavelet, kurtosis
Subjects: T Technology > TJ Mechanical engineering and machinery
Faculty/Division: Faculty of Mechanical Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 17 Dec 2014 06:47
Last Modified: 12 Jan 2018 01:44
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item