A neural network-based approach for detection of structural damage

Ching Yun Kao*, Shih-Lin Hung

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations

Abstract

This work presents a novel neural network based-approach for detecting structural damage. The proposed approach involves two steps. The first step, system identification, uses Neural System Identification Networks (NSINs) to identify the undamaged and damaged states of a structural system. The second step, structural damage detection, uses the aforementioned trained NSINs to generate free vibration responses with the same initial condition or impulsive force. Comparing the period and amplitude of the free vibration responses of the damaged and undamaged states allows the extent of changes to be assessed. An experimental example demonstrates the feasibility of applying the proposed method for detecting structural damage.

Original languageEnglish
Article number459-070
Pages (from-to)251-256
Number of pages6
JournalProceedings of the IASTED International Conference on Modelling and Simulation
StatePublished - May 2005
Event16th IASTED International Conference on Modelling and Simulation - Cancun, Mexico
Duration: 18 May 200520 May 2005

Keywords

  • Building structures
  • Damage detection
  • Neural networks
  • System identification

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