샌드위치 복합재의 결함 탐지 및 정량화를 위한 일치 추적 분해 기반 디노이징 기법 개발

Matching Pursuit Decomposition-Based Signal Denoising to Detect and Quantify the Delamination of Sandwich Composites
  • 김준영
  • 기대연
  • 박규태
  • 최하람
  • 김흥수
Citations

SCOPUS

0

초록

In this paper, a damage detection and quantification method for sandwich composites using matching pursuit decomposition (MPD) is presented. Sandwich composites with and without delamination were fabricated using the hand lay-up and hot-press methods, and the location and size of delamination were confirmed using flash thermography. An ultrasonic wave propagation experiment using the pitch-catch method was set up to collect data from healthy and damaged samples. The acquired signals were estimated and decomposed using MPD and compared with signals denoised using fast Fourier and wavelet transforms. The denoised signals were trained by a 1-D CNN model with the same number of layers and filters.. The proposed method showed improved accuracy and stability than the traditional method. In addition, more reliable mode separation in the time-frequency representation could be confirmed, extending the possibility of MPD-based signal preprocessing in deep learning training.

키워드

matching pursuit decompositionsandwich compositedeep learningsignal preprocessing일치 추적 분해샌드위치 복합재딥러닝신호 전처리
제목
샌드위치 복합재의 결함 탐지 및 정량화를 위한 일치 추적 분해 기반 디노이징 기법 개발
제목 (타언어)
Matching Pursuit Decomposition-Based Signal Denoising to Detect and Quantify the Delamination of Sandwich Composites
저자
김준영기대연박규태최하람김흥수
DOI
10.7734/COSEIK.2024.37.5.295
발행일
2024-10
저널명
한국전산구조공학회논문집
37
5
페이지
295 ~ 300