Pattern Recognition Approach Of Stress Wave Propagation In Carbon Steel Tubes For Defect Detection

Abd Halim, Zakiah and Jamaludin, Nordin and Junaidi, Syarif and Syed Yusainee, Syed Yahya (2015) Pattern Recognition Approach Of Stress Wave Propagation In Carbon Steel Tubes For Defect Detection. International Journal of Computer Theory and Engineering, 7. pp. 139-144. ISSN 1793-8201

Text 2015 IJCTE.pdf - Submitted Version Download (834kB)

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.

Item Type:	Article
Uncontrolled Keywords:	Auto-regressive, pattern recognition, principal component analysis, stress wave.
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Mechanical Engineering
Depositing User:	Muhammad Afiz Ahmad
Date Deposited:	31 Mar 2017 00:50
Last Modified:	20 Jul 2021 17:53
URI:	http://eprints.utem.edu.my/id/eprint/18166
Statistic Details:	View Download Statistic

Actions (login required)

View Item