A bayesian probabilistic approach for structural damage detection

Y. H. Wei, Y. Q. Ni, Q. A. Wang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Measured structural dynamic response is very helpful for structural health monitoring (SHM). However, the response signals that contain damage information of a structure is difficult to obtain. In other words, traditional classification methods are difficult to be applied to determine structural damage effectively. In this study, a Bayesian-based method that uses only, at model training stage, the information on structural response under healthy conditions is proposed for damage detection, followed by verification of the proposed method by referring to a simulated structure. A frequencydomain health condition index (HCI) is first formulated via a linear transformation. By applying sparse Bayesian learning (SBL) and relevance vector machine (RVM), regression models about the real and imaginary parts of HCI are then established. A quantitative analysis of residuals between the predicted HCI and actual HCI is used as a measure for damage identification. If the predicted HCI deviates considerably from the actual HCI, the damage is identified. By evaluating the simulated structure under different damage conditions, the effectiveness of the proposed method for structural damage detection is verified.

Original languageEnglish
Title of host publication9th International Conference on Structural Health Monitoring of Intelligent Infrastructure
Subtitle of host publicationTransferring Research into Practice, SHMII 2019 - Conference Proceedings
EditorsGenda Chen, Sreenivas Alampalli
PublisherInternational Society for Structural Health Monitoring of Intelligent Infrastructure, ISHMII
Pages1292-1297
Number of pages6
ISBN (Electronic)9780000000002
Publication statusPublished - 2019
Event9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII 2019 - St. Louis, United States
Duration: 4 Aug 20197 Aug 2019

Publication series

Name9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII 2019 - Conference Proceedings
Volume2

Conference

Conference9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII 2019
CountryUnited States
CitySt. Louis
Period4/08/197/08/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Civil and Structural Engineering
  • Building and Construction

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