Damage detection of a plate with multiple cracks by two-dimensional discrete wavelet transforms and artificial neural network

J. M. Yang, Y. H. Yen, K. L. Lin

Research output: Contribution to journalArticlepeer-review

Abstract

Structural damage detection has been a very important issue in engineering. If damages can be detected in a timely manner, many disasters can be prevented. In recent years, wavelet transform methods and artificial neural network have been widely used in Non-Destructive Testing. The present investigation, at first the two-dimensional discrete wavelet transform method to detect the position of cracks in plate. Secondly, the artificial neural network along with the two-dimensional discrete wavelet transform method is used to identify the degree of damage in this study. During the numerical simulation, different from the previous study, only the area around a single crack is selected and used to calculated the damage indexes for a single crack on a plate. The obtained damage indexes are used as training sample for artificial neural network analysis, which then are utilized to evaluate the degree of damage of a single crack on a multiple cracks plate. In the experiment analysis, in order to eliminated the mode shapes, difference between simulations and experiments, the mode shapes of a perfect simulated plate and a plate without cracks used in experiment are studied. It is our intention to obtain more precise method to estimate the degree of damage of cracks on plate.

Original languageEnglish
Pages (from-to)77-91
Number of pages15
JournalJournal of Taiwan Society of Naval Architects and Marine Engineers
Volume33
Issue number2
Publication statusPublished - 2014 May 1

All Science Journal Classification (ASJC) codes

  • Ocean Engineering
  • Mechanical Engineering

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