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Smart Structures and Systems
  Volume 30, Number 4, October 2022 , pages 339-351
DOI: https://doi.org/10.12989/sss.2022.30.4.339
 


Structural system identification by measurement error-minimization observability method using multiple static loading cases
Jun Lei, Jose Antonio Lozano-Galant, Dong Xu, Feng-Liang Zhang and Jose Turmo

 
Abstract
    Evaluating the current condition of existing structures is of primary importance for economic and safety reasons. This can be addressed by Structural System Identification (SSI). A reliable static SSI depends on well-designed sensor configuration and loading cases, as well as efficient parameter estimation algorithms. Static SSI by the Measurement Error-Minimizing Observability Method (MEMOM) is a model-based deterministic static SSI method that could estimate structural parameters from static responses. In the current state of the art, this method is only applicable when structures are subjected to one loading case. This might lead to lack of information in some local regions of the structure (such as the null curvatures zones). To address this issue, the SSI by MEMOM using multiple loading cases is proposed in this work. Observability equations obtained from different loading cases are concatenated simultaneously and an optimization procedure is introduced to obtain the estimations by minimizing the discrepancy between the predicted response and the measured one. In addition, a Genetic-Algorithm (GA)-based Optimal Sensor Placement (OSP) method is proposed to tackle the OSP problem under multiple static loading cases for the very first time. In this approach, the Fisher Information Matrix (FIM)'s determinant is used as the metric of the goodness of sensor configurations. The numerical examples of a 3-span continuous bridge and a 13-story frame, are analyzed to validate the applicability of the extended SSI by MEMOM and the GA-based OSP method.
 
Key Words
    genetic algorithm; measurement errors; multiple loading cases; observability method; static response; optimization; stiffness matrix method; structural system identification
 
Address
(1) Jun Lei, Feng-Liang Zhang:
Key Laboratory of Earthquake Engineering and Engineering Vibration, Institute of Engineering Mechanics, China Earthquake Administration, Harbin 150086, China;
(2) Jun Lei, Feng-Liang Zhang:
Key Laboratory of Earthquake Disaster Mitigation, Ministry of Emergency Management, China;
(3) Jun Lei, Feng-Liang Zhang:
School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen, China;
(4) Jose Antonio Lozano-Galant:
Department of Civil Engineering, University of Castilla-La Mancha, Ciudad, Real, Spain;
(5) Dong Xu:
Department of Bridge Engineering, Tongji University, Shanghai, China;
(6) Jose Turmo:
Department of Civil and Environmental Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain.
 

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