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Identification Methods for Structural Health Monitoring

  • Book
  • © 2016

Overview

Editors:
  1. Eleni Chatzi

    1. Dept. of Civil, Envi. & GoematicEng., ETH Zürich, Zürich, Switzerland

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    You can also search for this editor in PubMed   Google Scholar

  2. Costas Papadimitriou

    1. University of Thessaly, Volos, Greece

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    You can also search for this editor in PubMed   Google Scholar

  • Providing an overview of system identification techniques customized to fit the specific purpose of SHM
  • Illustrates the application of presented methodologies on actual field structures
  • Providing state-of-the-art in the field
  • Includes supplementary material: sn.pub/extras

Part of the book series: CISM International Centre for Mechanical Sciences (CISM, volume 567)

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Table of contents (6 chapters)

  1. Front Matter

    Pages i-ix
    Download chapter PDF

  2. Implementation of Identification Methodologies on Large-Scale Structures

    • Vincenzo Gattulli
    Pages 1-34

  3. Efficient Data Fusion and Practical Considerations for Structural Identification

    • Andrew W. Smyth, Thaleia Kontoroupi, Patrick T. Brewick
    Pages 35-49

  4. Implementation of Parametric Methods for the Treatment of Uncertainties in Online Identification

    • Eleni N. Chatzi, Minas D. Spiridonakos, Andrew W. Smyth
    Pages 51-87

  5. Bayesian Parameter Estimation

    • E. Simoen, G. Lombaert
    Pages 89-115

  6. Bayesian Operational Modal Analysis

    • S. K. Au
    Pages 117-135

  7. Bayesian Uncertainty Quantification and Propagation (UQ+P): State-of-the-Art Tools for Linear and Nonlinear Structural Dynamics Models

    • Costas Papadimitriou
    Pages 137-170
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Keywords

About this book

The papers in this volume provide an introduction to well known and established system identification methods for structural health monitoring and to more advanced, state-of-the-art tools, able to tackle the challenges associated with actual implementation. Starting with an overview on fundamental methods, introductory concepts are provided on the general framework of time and frequency domain, parametric and non-parametric methods, input-output or output only techniques. Cutting edge tools are introduced including, nonlinear system identification methods; Bayesian tools; and advanced modal identification techniques (such as the Kalman and particle filters, the fast Bayesian FFT method). Advanced computational tools for uncertainty quantification are discussed to provide a link between monitoring and structural integrity assessment. In addition, full scale applications and field deployments that illustrate the workings and effectiveness of the introduced monitoring schemes are demonstrated.

Editors and Affiliations

  • Dept. of Civil, Envi. & GoematicEng., ETH Zürich, Zürich, Switzerland

    Eleni Chatzi

  • University of Thessaly, Volos, Greece

    Costas Papadimitriou

Bibliographic Information

  • Book Title: Identification Methods for Structural Health Monitoring

  • Editors: Eleni Chatzi, Costas Papadimitriou

  • Series Title: CISM International Centre for Mechanical Sciences

  • DOI: https://doi.org/10.1007/978-3-319-32077-9

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: CISM International Centre for Mechanical Sciences 2016

  • Hardcover ISBN: 978-3-319-32075-5Published: 03 June 2016

  • Softcover ISBN: 978-3-319-81190-1Published: 30 May 2018

  • eBook ISBN: 978-3-319-32077-9Published: 25 May 2016

  • Series ISSN: 0254-1971

  • Series E-ISSN: 2309-3706

  • Edition Number: 1

  • Number of Pages: IX, 170

  • Number of Illustrations: 14 b/w illustrations, 39 illustrations in colour

  • Topics: Building Repair and Maintenance

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