Damage detection in smart composite structures using low frequency structural vibration

Asif Khan, Heung Soo Kim, Jung Woo Sohn

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Output-only based damage assessment of delaminated smart composite structures is increasingly appealing due to its easy availability in real engineering applications. In this work, structural vibration responses of the pristine and delaminated composite structures are processed via Fast Fourier Transform (FFT) and Convolutional Neural Network (CNN) for the classification of healthy and various damaged cases. The dynamic model for the healthy and delaminated smart composite laminates is developed by incorporating of improved layerwise theory, higher-order electric potential field, and finite element method. Structural vibration responses are obtained through a surface bonded piezoelectric sensor by solving the electromechanically coupled dynamic model in the time domain. FFT is used to construct vibration-based images from the transient responses of the sensor and CCN is used to classify those images into healthy and damaged classes. The confusion matrix of CNN showed physically consistent results and an overall classification accuracy of 90% was obtained. The pre-trained CNN was also tested to predict labels for new cases of delaminations in the smart composite laminates. The essence of the proposed method is that it requires only low-frequency structural vibration responses for the detection and localization of delamination in smart composite laminates.

Original languageEnglish
Title of host publicationNano-, Bio-, Info-Tech Sensors, and 3D Systems IV
EditorsJaehwan Kim
PublisherSPIE
ISBN (Electronic)9781510635333
DOIs
StatePublished - 2020
EventNano-, Bio-, Info-Tech Sensors, and 3D Systems IV 2020 - None, United States
Duration: 27 Apr 20208 May 2020

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11378
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceNano-, Bio-, Info-Tech Sensors, and 3D Systems IV 2020
Country/TerritoryUnited States
CityNone
Period27/04/208/05/20

Keywords

  • Deep learning
  • Delamination
  • Smart composite laminates
  • Structural vibration

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