Statistical Signal Processing and Sorting for Acoustic Emission Monitoring of High-Temperature Pressure Components

Hrairi, Meftah (2009) Statistical Signal Processing and Sorting for Acoustic Emission Monitoring of High-Temperature Pressure Components. Experimental Techniques, 33 (5). pp. 35-43. ISSN 1747-1567

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Abstract

A study was conducted to demonstrate feasibility of designing and developing a reliable and real-time monitoring methodology based on statistical pattern recognition for early detection of defects in small, low-alloy steel vessels. These low-alloy steel vessels were pressurized at high temperature with an aqueous hydrogen sulfide solution. A portable acoustic emission (AE) system was used to capture emission signals. An in-house-developed FORTRAN program calculated 37 features, including 18 from the time domain signal and 19 from the frequency domain. SAS statistical software package was used to find a correlation between these features, leading to the classification of AE signals according to type and discover relationships between emissions and the findings of the investigation. The specimens used in the study were made of low-alloy steel with similar characteristics to those used by petroleum refineries.

Item Type:	Article (Journal)
Additional Information:	4980/6536
Uncontrolled Keywords:	AE, Acoustic emission, Statistical signal processing
Subjects:	T Technology > TJ Mechanical engineering and machinery
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechanical Engineering
Depositing User:	Prof. Dr. Meftah Hrairi
Date Deposited:	02 Dec 2011 11:16
Last Modified:	23 Dec 2011 16:41
URI:	http://irep.iium.edu.my/id/eprint/6536

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