All Issue

2024 Vol.37, Issue 5

Research Paper

Matching Pursuit Decomposition-Based Signal Denoising to Detect and Quantify the Delamination of Sandwich Composites

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

Jun Young Kim1
,
Daeyeon Ki2
,
Kyutae Park2
,
Haram Choi2
,
Heung Soo Kim3*
김 준영1
,
기 대연2
,
박 규태2
,
최 하람2
,
김 흥수3*
1Graduate Research Student, Department of Mechanical, Robotics and Energy Engineering, Dongguk University, Seoul, 04620, Korea
2Undergraduate Research Students, Department of Mechanical, Robotics and Energy Engineering, Dongguk University, Seoul, 04620, Korea
3Professor, Department of Mechanical, Robotics and Energy Engineering, Dongguk University, Seoul, 04620, Korea
1동국대학교 기계로봇에너지공학과 석사후연구원
2동국대학교 기계로봇에너지공학과 학부연구원
3동국대학교 기계로봇에너지공학과 교수
*Corresponding Author
31 October 2024. pp. 295-300
PDF XML Citation
Abstract

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.

Keywords
matching pursuit decomposition
sandwich composite
deep learning
signal preprocessing

본 논문에서는 일치 추적 분해를 활용한 샌드위치 복합재의 결함 탐지 및 정량화 방법을 소개한다. 샌드위치 복합재 시편을 제작하기 위해 핸드 레이-업 공법과 핫 프레스 공법을 활용하여 결함이 존재하는 시편과 없는 시편을 제작하였다. 결함의 위치와 정도를 파악하기 위해 플래시 서모그래피를 활용하여 확인하였다. 각각의 시편에서 데이터를 확보하기 위해 pitch-catch법을 활용한 초음파 전파 실험을 설정하였고, 샌드위치 복합재의 표면에 부착한 압전 센서를 통해 데이터를 확보하였다. 획득한 신호는 일치 추적 분해를 이용하여 추정 및 분해하고, 고속 푸리에 변환과 웨이블릿 변환 기반 노이즈 제거 방법과의 성능을 비교하였다. 노이즈를 제거한 신호는 각각 동일한 구조의 1-D CNN 모델에 훈련하여 성능을 비교하였다. 제안한 일치 추적 분해 기반 신호 노이즈 제거는 기존의 방법보다 높은 정확도, 안정성, 훈련 속도를 보였으며, 시간-주파수 영역에서 보다 직관적인 모드 분리를 확인하여 특성 추출을 통한 일치 추적 분해 기반 신호 전처리 및 딥러닝 모델 훈련의 가능성을 확장할 수 있음을 확인하였다.

키워드
일치 추적 분해
샌드위치 복합재
딥러닝
신호 전처리
References
1

Agarwal, S., Mitra, M. (2014) Lamb Wave Based Automatic Damaged Detection using Matching Pursuit and Machine Learning, Smart Mater. Struct., 23, p.085012.

10.1088/0964-1726/23/8/085012
2

Cui, L., Kang, C., Wang, H., Chen, P. (2011) Application of Composite Dictionary Multi-Atom Matching in Gear Fault Diagnosis, Sensors, 11(6), pp.5981-6002.

10.3390/s110605981
3

Guo, J., Zeng, X., Liu, Q., Qing, X. (2022) Lamb Wave-Based Damage Localization and Quantification in Composites Using Probabilistic Imaging Algorithm and Statistical Method, Sensors, 22(13), p.4810.

10.3390/s22134810
4

Hay, T.R., Wei, L., Rose, J.L. (2003) Rapid Inspection of Composite Skin-Honeycomb Core Structures with Ultrasonic Guided Waves, J. Compos. Mater., 37(10), pp.929~939.

10.1177/0021998303037010005
5

Khalid, S., Kim, H.S. (2019) Progressive Damage Modeling of Inter and Intra Laminar Damaged in Open Hole Tensil Composite Laminates, J. Comput. Struct. Eng. Inst. Korea, 32(4), pp.233-240.

10.7734/COSEIK.2019.32.4.233
6

Khan, A., Kim, H.S. (2022) A Brief Overview of Delamination Localization in Laminated Composites, Multiscale Sci. & Eng., 4(3), pp.102-110.

10.1007/s42493-022-00085-w
7

Kim, H., Yuan, F. (2022) Adaptiva Signal Decomposition and Dispersion Removal based on the Matching Pursuit Algorithm using Dispersion-based Dictionary for Enhancing Damage Imaging, Ultrasonics, 103, p.106087

10.1016/j.ultras.2020.106087
8

Li, T., Su, J., Li, N., Xu, H., Chang, Y. (2023) Investigation of Wind Turbine Blade Ultrasonic Pulse-Echo Signal Decomposition based on the Matching Pursuit Algorithm. Insight-Non-Destr. Test. & Cond. Monit., 65(3), pp.133-138.

10.1784/insi.2023.65.3.133
9

Li, Y., Yao, K., Li, X. (2022) An Ultrasonic Signal Reconstruction Algorithm of Multilayer Composites in Non-Destructive Testing, Appl. Acoust., 186, p.108461.

10.1016/j.apacoust.2021.108461
10

Mallat, S.G., Zhang, Z. (1993) Matching Pursuit With Time-Frequency Dictionaries, IEEE Trans. Signal Process., 41(12), pp.3397~3415.

10.1109/78.258082
11

Xu, B., Giurgiutiu, V., Yu, L. (2009) Lamb Waves Decomposition and Mode Identification using Matching Pursuit Method, Sensors & Smart Struct. Tech. for Civil, Mech. & Aerosp. Syst., 7292, pp.161~172.

10.1117/12.816087
Information
  • Publisher :Computational Structural Engineering Institute of Korea
  • Publisher(Ko) :한국전산구조공학회
  • Journal Title :Journal of the Computational Structural Engineering Institute of Korea
  • Journal Title(Ko) :한국전산구조공학회 논문집
  • Volume : 37
  • No :5
  • Pages :295-300
  • Received Date : 2024-05-09
  • Revised Date : 2024-07-16
  • Accepted Date : 2024-07-26
  • DOI :https://doi.org/10.7734/COSEIK.2024.37.5.295
Journal Informaiton Journal of the Computational Structural Engineering Institute of Korea Journal of the Computational Structural Engineering Institute of Korea
Online Submission
  • NRF
  • KOFST
  • crossref crossmark
  • crossref cited-by
  • crosscheck
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close