Adhesive Area Detection System of Single-Lap Joint Using Vibration-Response-Based Nonlinear Transformation Approach for Deep Learning

Min-Je Kim; Dong-Yoon Kim; Gil Ho Yoon

doi:10.7734/COSEIK.2023.36.1.57

All Issue

2023 Vol.36, Issue 1 Preview Page Next Page

Research Paper

Adhesive Area Detection System of Single-Lap Joint Using Vibration-Response-Based Nonlinear Transformation Approach for Deep Learning 딥러닝을 이용하여 진동 응답 기반 비선형 변환 접근법을 적용한 단일 랩 조인트의 접착 면적 탐지 시스템

28 February 2023. pp. 57-65

PDF XML

Abstract

A vibration response-based detection system was used to investigate the adhesive areas of single-lap joints using a nonlinear transformation approach for deep learning. In industry or engineering fields, it is difficult to know the condition of an invisible part within a structure that cannot easily be disassembled and the conditions of adhesive areas of adhesively bonded structures. To address these issues, a detection method was devised that uses nonlinear transformation to determine the adhesive areas of various single-lap-jointed specimens from the vibration response of the reference specimen. In this study, a frequency response function with nonlinear transformation was employed to identify the vibration characteristics, and a virtual spectrogram was used for classification in convolutional neural network based deep learning. Moreover, a vibration experiment, an analytical solution, and a finite-element analysis were performed to verify the developed method with aluminum, carbon fiber composite, and ultra-high-molecular-weight polyethylene specimens.

Keywords

nonlinear transformation

frequency response function

adhesive area

convolutional neural network

본 연구는 딥러닝을 위한 비선형 변환 접근법을 사용하여 Single-lap joint의 접착 영역을 조사하기 위한 진동 응답 기반 탐지 시스템을 제시한다. 산업 혹은 공학 분야에서 분해가 쉽지 않은 구조 내에 보이지 않는 부분의 상태와 접착된 구조의 접착 부위 상태를 알기 어려운 문제가 있다. 이러한 문제를 해결하기 위해 본 연구는 비선형 변환을 이용하여 기준 시편의 진동 응답으로 다양한 시편의 접착 면적을 조사하는 탐지 방법을 제안한다. 이 연구에서는 CNN 기반 딥러닝으로 진동 특성을 파악하기 위해 비선형 변환을 적용한 주파수 응답 함수를 사용했고 분류를 위해 가상의 스펙트로그램을 사용했다. 또한, 제시된 방법을 검증하기 위해 알루미늄, 탄소섬유복합재 그리고 초고분자량 폴리에틸렌 시편에 대한 진동 실험, 분석적 해, 유한요소해석을 수행했다.

키워드

비선형 변환

주파수 응답 함수

접착 면적

합성곱 신경망

References

Bauchau, O.A., Craig, J.I. (2009) Euler-Bernoulli Beam Theory, Struct. Anal., pp.173~221. 10.1007/978-90-481-2516-6_5

Du, Y., Shi, L. (2014) Effect of Vibration Fatigue on Modal Properties of Single Lap Adhesive Joints, Int. J. Adhes. & Adhes., 53, pp.72~79. 10.1016/j.ijadhadh.2014.01.007

Kim, D.Y., Woo, Y.J., Kang, K., Yoon, G.H. (2022) Failure Diagnosis System using a New Nonlinear Mapping Augmentation approach for Deep Learning Algorithm, Mech. Syst. & Signal Proc., 172, 108914. 10.1016/j.ymssp.2022.108914

LeCun, Y., Bengio, Y., Hinton, G. (2015) Deep Learning, Nature, 521(7553), pp.436~444. 10.1038/nature1453926017442

Nguyen, L.H., Lässig, T.R., Ryan, S., Riedel, W., Mouritz, A.P., Orifici, A.C. (2016) A Methodology for Hydrocode Analysis of Ultra-High Molecular Weight Polyethylene Composite under Ballistic Impact, Compos. Part A: Appl. Sci. & Manuf., 84, pp.224~235. 10.1016/j.compositesa.2016.01.014

Oosterom, R., Ahmed, T.J., Poulis, J.A., Bersee, H.E.N. (2006) Adhesion Performance of UHMWPE after Different Surface Modification Techniques, Med. Eng. & Phys., 28(4), pp. 323~330. 10.1016/j.medengphy.2005.07.00916118059

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 : 36
No :1
Pages :57-65
Received Date : 2023-01-04
Revised Date : 2023-02-05
Accepted Date : 2023-02-06
DOI :https://doi.org/10.7734/COSEIK.2023.36.1.57

Journal of the Computational Structural Engineering Institute of Korea ISSN:1229-3059(Print) 2287-2302(Online) 한국전산구조공학회 논문집

All Issue