4.7 Article

The role of modal parameters uncertainty estimation in automated modal identification, modal tracking and data normalization

Journal

ENGINEERING STRUCTURES
Volume 224, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.engstruct.2020.111208

Keywords

Dam monitoring; Operational modal analysis; Uncertainties in modal properties; Modal tracking

Funding

  1. Project CONSTRUCT - Institute of R&D In Structures and Construction [POCI-01-0145-FEDER-007457]
  2. Project Advanced Online Dynamic Structural Health Monitoring of Concrete Dams [PTDC/ECM-EST/0805/2014\16761 - DAM_AGE]
  3. FEDER funds through COMPETE2020 - Programa Operacional Competitividade e Internacionalizacao (POCI)
  4. FCT - Fundacao para a Ciencia e a Tecnologia
  5. FCT [SFRH/BD/100587/2014]
  6. EDP Producao
  7. Fundação para a Ciência e a Tecnologia [SFRH/BD/100587/2014] Funding Source: FCT

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During the last decade, many vibration-based structural health monitoring systems have been successfully implemented in different structures such as bridges, towers, stadia and wind turbines, with the aim of studying the structure dynamics and its evolution over time, eventually detecting the occurrence of novel structural behaviour that may indicate the presence of damage. Such vibration-based monitoring systems generally rely on the identification of modal properties, which are then used as monitoring features. Therefore, from operational modal analysis to the tracking of those features and finally to data normalization, many processing steps occur that depend on the accuracy of the identified modal properties. Thus, the estimation of the uncertainties associated with the identified modal properties increases the robustness of this process. In this context, data obtained from the continuous dynamic monitoring of a concrete arch dam has been used to evaluate the gains of quantifying the uncertainties of modal properties, evaluating in particular the effect of taking these uncertainties into consideration when performing automated operational modal analysis, modal tracking and data normalization. Nevertheless, it is observed that the most significant gains of considering estimates uncertainties occur when these quantities are used for removing outliers during modal tracking.

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