Detection of tube defect using the autoregressive algorithm

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

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Easy detection and evaluation of defect in the tube structure is a continuous problem and remains a significant demand in tube inspection technologies. This study is aimed to automate defect detection using the pattern recognition approach based on the classification of high frequency stress wave signals. The stress wave signals from vibrational impact excitation on several tube conditions were captured to identify the defect in ASTM A179 seamless steel tubes. The variation in stress wave propagation was captured by a high frequency sensor. Stress wave signals from four tubes with artificial defects of different depths and one reference tube were classified using the autoregressive (AR) algorithm. The results were demonstrated using a dendrogram. The preliminary research revealed the natural arrangement of stress wave signals were grouped into two clusters. The stress wave signals from the healthy tube were grouped together in one cluster and the signals from the defective tubes were classified in another cluster. This approach was effective in separating different stress wave signals and allowed quicker and easier defect identification and interpretation in steel tubes.

Original languageEnglish
Pages (from-to)131-152
Number of pages22
JournalSteel and Composite Structures
Volume19
Issue number1
DOIs
Publication statusPublished - 1 Jul 2015

Fingerprint

Defects
Steel
Wave propagation
Pattern recognition
Inspection
Sensors

Keywords

  • Autoregressive
  • Defect identification
  • Impact excitation
  • Pattern recognition
  • Stress wave

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Metals and Alloys

Cite this

Detection of tube defect using the autoregressive algorithm. / Halim, Zakiah A.; Jamaludin, Nordin; Junaidi, Syarif; Yusainee, Syed.

In: Steel and Composite Structures, Vol. 19, No. 1, 01.07.2015, p. 131-152.

Research output: Contribution to journalArticle

Halim, Zakiah A. ; Jamaludin, Nordin ; Junaidi, Syarif ; Yusainee, Syed. / Detection of tube defect using the autoregressive algorithm. In: Steel and Composite Structures. 2015 ; Vol. 19, No. 1. pp. 131-152.
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