4.7 Article

Continuous dynamic monitoring of a large-span arch bridge with wireless nodes based on MEMS accelerometers

Journal

STRUCTURAL CONTROL & HEALTH MONITORING
Volume 29, Issue 7, Pages -

Publisher

JOHN WILEY & SONS LTD
DOI: 10.1002/stc.2963

Keywords

automated operational modal analysis; data synchronization; MEMS accelerometers; SHM; wireless sensors

Funding

  1. European Regional Development Fund [NORTE01-0247-FEDER-033511]
  2. FCT/MCTES (PIDDAC) [PTDC/ECI-EST/29558/2017, UIDB/04708/2020]
  3. Zhejiang Provincial Education Department of China [Y201430581]
  4. Zhejiang Provincial Natural Science Foundation of China [LQ16E080009]
  5. National Natural Science Foundation of China [51705114]
  6. Fundação para a Ciência e a Tecnologia [PTDC/ECI-EST/29558/2017] Funding Source: FCT

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This paper presents the application of MEMS accelerometers and wireless nodes in continuous dynamic monitoring of an arch bridge and evaluates their ability to automatically track the bridge modal properties. The proposed algorithms enable the wireless data acquisition system to meet the requirements for continuous dynamic monitoring.
The high cost of conventional monitoring systems limits their application range. In this paper, microelectromechanical system (MEMS) accelerometers are adopted together with wireless nodes developed in the Faculty of Engineering, University of Porto (FEUP), in the continuous dynamic monitoring of an arch bridge, and their ability for automated tracking of the bridge modal properties is evaluated. In order to optimize the system autonomy and make the installation more flexible, the wireless nodes do not include hardware for online time synchronization. Therefore, the data synchronization has to be achieved in the data processing. In this context, the present paper includes the following features: (1) analysis of the influence of lack of synchronization on operational modal analysis; (2) proposal of a procedure for automatic estimation of modal properties using an index named pole similarity index to distinguish mathematical poles from physical modes and density-based spatial clustering; and (3) the use of a new data synchronization method to be applied together with system identification algorithms. After the presentation and validation of the devised processing tools, it performed a comparison of the identification results obtained by the wireless MEMS system and a high-cost commercial data acquisition system to evaluate the capability of the developed hardware for continuous dynamic monitoring. It is demonstrated that with the help of the proposed algorithms, the wireless data acquisition system meets the requirements for continuous dynamic monitoring.

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