Identification Methods for Structural Health Monitoring

  • Eleni Chatzi
  • Costas Papadimitriou

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

Table of contents

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.


Bayesian Computational Techniques Nonlinear Structural Dynamics Models Parametric Identification Methods Structural Health Monitoring System Identification Techniques

Editors and affiliations

  • Eleni Chatzi
    • 1
  • Costas Papadimitriou
    • 2
  1. 1.Dept. of Civil, Envi. & GoematicEng.ETH ZürichZürichSwitzerland
  2. 2.University of ThessalyVolosGreece

Bibliographic information

  • DOI
  • Copyright Information CISM International Centre for Mechanical Sciences 2016
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-319-32075-5
  • Online ISBN 978-3-319-32077-9
  • Series Print ISSN 0254-1971
  • Series Online ISSN 2309-3706
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