Monitoring and Assessment of Acoustic Emission Signatures during Fatigue Mechanism of API5LX70 Gas Pipeline Steel

M.F. M. Yusof; N.  Jamaludin; S.  Abdullah; Z.H.  Hanafi; M.S. M. Zain

doi:10.15282/jmes.2.2012.11.0022

Authors

M.F. M. Yusof Faculty of Mechanical Engineering, Universiti Malaysia Pahang, 26600 UMP, Pekan, Pahang, Malaysia
N. Jamaludin Department of Mechanical and Materials Engineering Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor, Malaysia
S. Abdullah Department of Mechanical and Materials Engineering Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor, Malaysia
Z.H. Hanafi Department of Mechanical and Materials Engineering Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor, Malaysia
M.S. M. Zain Department of Mechanical and Materials Engineering Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor, Malaysia

DOI:

https://doi.org/10.15282/jmes.2.2012.11.0022

Keywords:

Acoustic emission, fatigue, API5L X70 steel, statistical parameter.

Abstract

The detection of early fatigue phenomena in a gas pipeline is crucial in order to avoid catastrophic consequences. Therefore, appropriate inspection is needed to assess fatigue phenomena in a gas pipeline system. Acoustic emission (AE) technology is expected to be suitable in this regard. This paper presents the monitoring and assessment of AE signatures of the fatigue mechanism of gas pipeline material, API 5L X70 steel. The stress amplitude of 65%, 60%, 58% and 53% of the ultimate tensile strength were done in order to observe AE activity during the fatigue mechanism. Field measurements were also done by investigating AE signatures of an operational gas pipeline for comparison purposes. Based on the correlation of the AE signatures and fatigue mechanism, it was found that the AE activities generated during the fatigue mechanism were divided into three different stages. Analysis of the AE features and statistical parameters have shown that the kurtosis values of the time domain AE signatures from the third stage of the fatigue mechanism were different from the field measurements. This results show that the application of the kurtosis was expected to be able to detect the time domain AE signatures from the crack stage.

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