Journal ArticleDOI
Nonlinear finite element model updating for damage identification of civil structures using batch Bayesian estimation
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TLDR
In this article, a framework for structural health monitoring (SHM) and damage identification of civil structures is presented, which integrates advanced mechanics-based nonlinear finite element (FE) modeling and analysis techniques with a batch Bayesian estimation approach to estimate time-invariant model parameters used in the FE model of interest.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 2017-02-01. It has received 92 citations till now. The article focuses on the topics: Uncertainty quantification & Structural health monitoring.read more
Citations
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Book
Parameter Sensitivity in Nonlinear Mechanics: Theory and Finite Element Computations
TL;DR: In this paper, the basic concepts of Nonlinear Quasi-Static Problems at Regular States are discussed. And the concepts of Shape Sensitivity and Post-Buckling are discussed as well.
Journal ArticleDOI
Review on the new development of vibration-based damage identification for civil engineering structures: 2010-2019
Rongrong Hou,Yong Xia +1 more
TL;DR: The progress in the area of vibration-based damage identification methods over the past 10 years is reviewed to help researchers and practitioners in implementing existing damage detection algorithms effectively and developing more reliable and practical methods for civil engineering structures in the future.
Journal ArticleDOI
The use of intelligent computational tools for damage detection and identification with an emphasis on composites – A review
Guilherme Ferreira Gomes,Yohan Alí Diaz Mendéz,Patricia da Silva Lopes Alexandrino,Sebastião Simões da Cunha,Antonio Carlos Ancelotti +4 more
TL;DR: The use of computational and intelligent techniques for structural monitoring in the form of a review with emphasis on composite materials is discussed, to help engineers and researchers find a starting point in developing a better solution to their specific structural monitoring problems.
Journal ArticleDOI
A Review of Vibration Based Inverse Methods for Damage Detection and Identification in Mechanical Structures Using Optimization Algorithms and ANN
Guilherme Ferreira Gomes,Yohan Alí Diaz Mendéz,Patricia da Silva Lopes Alexandrino,Sebastião Simões da Cunha,Antonio Carlos Ancelotti +4 more
TL;DR: In this article, the authors discuss the use of optimization algorithms and Artificial Neural Networks (ANN) for structural monitoring in the form of a brief review, which aims to help engineers and researchers find a better alternative to their specific structural monitoring problems.
Journal ArticleDOI
Bayesian nonlinear structural FE model and seismic input identification for damage assessment of civil structures
TL;DR: In this paper, an unscented Kalman filter is employed to estimate unknown time-invariant model parameters of a nonlinear finite element (FE) model of the structure and the unknown time histories of input excitations using spatially-sparse output response measurements recorded during an earthquake event.
References
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Book
System Identification: Theory for the User
TL;DR: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis and praktische Anwendung der verschiedenen Verfahren zur IdentifIZierung hat.
Journal ArticleDOI
Fundamentals of statistical signal processing: estimation theory
TL;DR: The Fundamentals of Statistical Signal Processing: Estimation Theory as mentioned in this paper is a seminal work in the field of statistical signal processing, and it has been used extensively in many applications.
Proceedings ArticleDOI
New extension of the Kalman filter to nonlinear systems
Simon Julier,Jeffrey Uhlmann +1 more
TL;DR: It is argued that the ease of implementation and more accurate estimation features of the new filter recommend its use over the EKF in virtually all applications.
Journal ArticleDOI
A new method for the nonlinear transformation of means and covariances in filters and estimators
TL;DR: A new approach for generalizing the Kalman filter to nonlinear systems is described, which yields a filter that is more accurate than an extendedKalman filter (EKF) and easier to implement than an EKF or a Gauss second-order filter.
Book
Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches
TL;DR: With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory.
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