Real time structural damage detection in the presence of deterministic operational power line noise

Basuraj Bhowmik, Budhaditya Hazra

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

1 Citation (Scopus)

Abstract

The application of real time structural damage detection schemes towards continuous monitoring of system health is an emerging topic of interest. This paper presents the use of real time algorithms belonging to the family of first order eigen perturbation (FOEP) techniques to detect damage, online. Integration of such algorithms towards numerical simulations and experimental validations shows promise in the field of structural health monitoring (SHM). However, the presence of operational noise arising during faults in experimentation, behaviour induced habits and AC voltage sources impedes the possibility of identifying the actual damage patterns. Towards this, the paper uses real time FOEP algorithms that essentially segregates the noise and the harmonic components from the mixed signal, thereby eliciting the vibrating components of the pure signal. Applications to both numerical simulations backed by experimental case studies demonstrate the utility of FOEP family of algorithms as ideal candidates for baseline free SHM.

Original languageEnglish
Title of host publication8th IOMAC - International Operational Modal Analysis Conference, Proceedings
EditorsSandro D. R. Amador, Rune Brincker, Evangelos I. Katsanos, Manuel Lopez Aenlle, Pelayo Fernandez
Pages213-221
Number of pages9
ISBN (Electronic)9788409049004
Publication statusPublished - 15 May 2019
Event8th International Operational Modal Analysis Conference, IOMAC 2019 - Copengahen, Denmark
Duration: 13 May 201915 May 2019

Publication series

Name8th IOMAC - International Operational Modal Analysis Conference, Proceedings

Conference

Conference8th International Operational Modal Analysis Conference, IOMAC 2019
Country/TerritoryDenmark
CityCopengahen
Period13/05/1915/05/19

Keywords

  • noise separation
  • online damage detection
  • operational noise
  • real time
  • time series analysis

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