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Investigation of modal identification and modal identifiability of a cable-stayed bridge with Bayesian framework
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  • Journal title : Smart Structures and Systems
  • Volume 17, Issue 3,  2016, pp.445-470
  • Publisher : Techno-Press
  • DOI : 10.12989/sss.2016.17.3.445
 Title & Authors
Investigation of modal identification and modal identifiability of a cable-stayed bridge with Bayesian framework
Kuok, Sin-Chi; Yuen, Ka-Veng;
 Abstract
In this study, the Bayesian probabilistic framework is investigated for modal identification and modal identifiability based on the field measurements provided in the structural health monitoring benchmark problem of an instrumented cable-stayed bridge named Ting Kau Bridge (TKB). The comprehensive structural health monitoring system on the cable-stayed TKB has been operated for more than ten years and it is recognized as one of the best test-beds with readily available field measurements. The benchmark problem of the cable-stayed bridge is established to stimulate investigations on modal identifiability and the present paper addresses this benchmark problem from the Bayesian prospective. In contrast to deterministic approaches, an appealing feature of the Bayesian approach is that not only the optimal values of the modal parameters can be obtained but also the associated estimation uncertainty can be quantified in the form of probability distribution. The uncertainty quantification provides necessary information to evaluate the reliability of parametric identification results as well as modal identifiability. Herein, the Bayesian spectral density approach is conducted for output-only modal identification and the Bayesian model class selection approach is used to evaluate the significance of different modes in modal identification. Detailed analysis on the modal identification and modal identifiability based on the measurements of the bridge will be presented. Moreover, the advantages and potentials of Bayesian probabilistic framework on structural health monitoring will be discussed.
 Keywords
Bayesian inference;structural health monitoring;cable-stayed bridge;modal identification;modal identifiability;
 Language
English
 Cited by
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Entropy-Based Optimal Sensor Placement for Model Identification of Periodic Structures Endowed with Bolted Joints, Computer-Aided Civil and Infrastructure Engineering, 2017, 32, 12, 1007  crossref(new windwow)
2.
Comparing Structural Identification Methodologies for Fatigue Life Prediction of a Highway Bridge, Frontiers in Built Environment, 2018, 3  crossref(new windwow)
3.
Relevance feature selection of modal frequency-ambient condition pattern recognition in structural health assessment for reinforced concrete buildings, Advances in Mechanical Engineering, 2016, 8, 8, 168781401666222  crossref(new windwow)
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