General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • APC: 800 USD
    • E-mail: ijcte@iacsitp.com
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Editor-in-chief
Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2015 Vol.7(2): 139-144 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2015.V7.945

Pattern Recognition Approach of Stress Wave Propagation in Carbon Steel Tubes for Defect Detection

Zakiah A. Halim, Nordin Jamaludin, Syarif Junaidi, and Syed Yusainee Syed Yahya

Abstract—The conventional stress wave signal interpretation in heat exchanger tube inspection is human dependent. The difficulties associated with accurate defect interpretations are skills and experiences of the inspector. Hence, in present study, alternative pattern recognition approach was proposed to interpret the presence of defect in carbon steel heat exchanger tubes SA179. Several high frequency stress wave signals propagated in the tubes due to impact are captured using Acoustic Emission method. In particular, one reference tube and two defective tubes were adopted. The signals were then clustered using the feature extraction algorithms. This paper tested two feature extraction algorithms namely Principal Component Analysis (PCA) and Auto-Regressive (AR). The pattern recognition results showed that the AR algorithm is more effective in defect identification. Good comparisons with the commonly global statistical analysis demonstrate the effective application of the present approach for defect detection.

Index Terms—Auto-regressive, pattern recognition, principal component analysis, stress wave.

A. H. Zakiah is with the Universiti Teknikal Malaysia Melaka, 76100 Melaka, Malaysia (e-mail: zakiahh@utem.edu.my).
N. Jamaludin and J. Syarif are with the Universiti Kebangsaan Malaysia, 43600 Bangi, Malaysia (e-mail: nordin@eng.ukm.my, syarif@eng.ukm.my).
S. Y. S. Yahya is with the Universiti Teknologi MARA, 40450 Shah Alam, Malaysia (e-mail: syedy237@salam.uitm.edu.my).

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Cite: Zakiah A. Halim, Nordin Jamaludin, Syarif Junaidi, and Syed Yusainee Syed Yahya, "Pattern Recognition Approach of Stress Wave Propagation in Carbon Steel Tubes for Defect Detection," International Journal of Computer Theory and Engineering vol. 7, no. 2, pp. 139-144, 2015.


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