Classification Analysis Of High Frequency Stress Wave For Autonomous Detection Of Defect In Steel Tubes

Abd Halim, Zakiah and Jamaludin, Nordin and Junaidi, Syarif and Syed Yahya, Syed Yusaini (2014) Classification Analysis Of High Frequency Stress Wave For Autonomous Detection Of Defect In Steel Tubes. AUSTRALIAN JOURNAL OF BASIC AND APPLIED SCIENCES, 8. pp. 251-257. ISSN 1991-8178

Text 2014 AJBAS.pdf - Published Version Download (310kB)

Abstract

Interpretation of propagated high frequency stress wave signals in steel tubes is noteworthy for defect identification.This paper demonstrated a successful new approach for autonomous defect detection in steel tubes using classification analysis of high frequency stress waves.Classification analysis using Principal Component Analysis (PCA) algorithm involved feature extraction to reduce the dimensionality of the complex stress waves propagation path.Two defective tubes containing a slot defect of different orientation and a reference tube are inspected using Vibration Impact Acoustic Emission (VIAE) technique.The tubes are externally excited using impact hammer.The variation of stress wave transmission path are captured by high frequency Acoustic Emission sensor.The propagated stress waves in the steel tubes are classified using PCA algorithm.Classification results are graphically illustrated using a dendrogram that demonstrated the arrangement of the natural clusters of the stress wave signals.The inspection of steel tubes showed good recognition of defect in circumferential and longitudinal orientation.This approach successfully classified stress wave signals from VIAE testing and provide fast and accurate defect identification of defective steel tubes from non-defective tubes.

Item Type:	Article
Uncontrolled Keywords:	Principal Component Analysis, classification analysis, defect recognition, stress wave, impact excitation
Subjects:	T Technology > T Technology (General) T Technology > TJ Mechanical engineering and machinery
Divisions:	Faculty of Mechanical Engineering
Depositing User:	Mohd. Nazir Taib
Date Deposited:	20 Dec 2018 14:00
Last Modified:	13 Jul 2021 02:52
URI:	http://eprints.utem.edu.my/id/eprint/21042
Statistic Details:	View Download Statistic

Actions (login required)

View Item