Acoustic Emission Pattern Recognition Method Utilizing Elastic Wave Simulation

• Arakawa Kenta

  School of Science and Technology, Meiji University

• Matsuo Takuma

  School of Science and Technology, Meiji University

抄録

Fracture mode analysis via acoustic emission (AE) has attracted research attention as a means of identifying the damage mechanism in machines and engineering structures. However, the estimation of relevant parameters from waveforms detected by AE sensors requires complex analysis because the waveforms are often distorted by the sensor response. Therefore, in this study, we develop a method for the classification of AE signals based on simulated AE waveforms. The simulated AE waveform is a convolution of the simulated elastic wave calculated via the 3D finite-difference time-domain (FDTD) method and the sensor response acquired with the use of the long bar method. The AE signals with different propagation angles obtained with the use of an epoxy-glass fiber composite specimen are classified, and wavelet contour maps and correlation coefficients are used for AE classification. The success of the AE classification is validated by the similarity of waveform features between the experiment and simulation.

収録刊行物

• MATERIALS TRANSACTIONS

  MATERIALS TRANSACTIONS 58 (10), 1411-1417, 2017

  公益社団法人 日本金属学会

キーワード

• acoustic emission
• finite-difference time-domain
• pattern recognition
• wavelet transform

詳細情報

• CRID: 1390282679231107712
• NII論文ID: 130006096688
• NII書誌ID: AA1151294X
• DOI: 10.2320/matertrans.m2017104
• ISSN: 13475320
• ISSN: 13459678
• NDL書誌ID: 028534732
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I028534732
• Web Site: https://www.jstage.jst.go.jp/article/matertrans/58/10/58_M2017104/_pdf
• 本文言語コード: en
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