Class activation map을 활용한 변위/변형률 정보 기반 구조물 손상 탐지 기법1

Translated title of the contribution: Displacement/Strain Based Structural Damage Detection Method Using Class Activation Map

Inho Jeong, Taeseong Kim, Haeseong Cho*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

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Abstract

Initial structural damage to a structure propagates and leads to failure. Detecting damage at an early stage is important to prevent failure. Recently, studies on measuring the displacement of a structure and predicting the strain field using digital image correlation (DIC) have been actively conducted. However, when the degree of damage is small or occurs in an area where stress is concentrated, it is difficult to identify it by visual inspection. Yet, it is impossible to process the real-time strain field data of large structures such as wind turbine blades, bridges, etc. In this paper, a novel real-time damage detection method using a class activation map (CAM) is developed. The CAM learns the relationship between strain field and structural damage location. After training is finished, the CAM is not only able to detect damage location from an untrained structural strain field, but also to print images of damage locations. The developed model predicts damage with 99.2 % accuracy.
Translated title of the contributionDisplacement/Strain Based Structural Damage Detection Method Using Class Activation Map
Original languageMultiple languages
Journal풍력에너지저널
Volume12
Issue number3
Pages (from-to)45-54
Number of pages10
ISSN2733-9467
DOIs
Publication statusPublished - 2021

Keywords

  • 손상탐지
  • 디지털영상처리
  • 분류 활성도맵
  • 구조건전성 모니터링
  • 인공신경망

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