Online Damage Detection in Structural Systems

Applications of Proper Orthogonal Decomposition, and Kalman and Particle Filters

  • Saeed Eftekhar Azam
Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Saeed Eftekhar Azam
    Pages 1-5
  3. Saeed Eftekhar Azam
    Pages 123-127
  4. Back Matter
    Pages 129-135

About this book

Introduction

This monograph assesses in depth the application of recursive Bayesian filters in structural health monitoring. Although the methods and algorithms used here are well established in the field of automatic control, their application in the realm of civil engineering has to date been limited. The monograph is therefore intended as a reference for structural and civil engineers who wish to conduct research in this field. To this end, the main notions underlying the families of Kalman and particle filters are scrutinized through explanations within the text and numerous numerical examples. The main limitations to their application in monitoring of high-rise buildings are discussed, and a remedy based on a synergy of reduced order modeling (based on proper orthogonal decomposition) and Bayesian estimation is proposed. The performance and effectiveness of the proposed algorithm is demonstrated via pseudo-experimental evaluations.

Keywords

Kalman Filter Particle Filter Proper Orthogonal Decomposition Stochastic Inverse Analysis Structural Health Monitoring

Authors and affiliations

  • Saeed Eftekhar Azam
    • 1
  1. 1.Road, Housing and Urban Development Research CenterTehranIran

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-02559-9
  • Copyright Information The Author(s) 2014
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-02558-2
  • Online ISBN 978-3-319-02559-9
  • Series Print ISSN 2191-530X
  • Series Online ISSN 2191-5318
  • About this book