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Wednesday, July 29, 2020 | History

3 edition of Structural identification and damage detection using genetic algorithms found in the catalog.

Structural identification and damage detection using genetic algorithms

Chan Ghee Koh

Structural identification and damage detection using genetic algorithms

by Chan Ghee Koh

  • 361 Want to read
  • 1 Currently reading

Published by CRC Press in Boca Raton .
Written in English


Edition Notes

Includes bibliographical references and index.

StatementC.G. Koh and M.J. Perry
SeriesStructures and infrastructures series -- v. 6
ContributionsPerry, M. J. (Michael J.), 1981-
Classifications
LC ClassificationsTA646 .K56 2010
The Physical Object
Paginationp. cm.
ID Numbers
Open LibraryOL24462209M
ISBN 109780415461023, 9780203859438
LC Control Number2009038174

1. Introduction. System Identification (SI) is the process of modeling an unknown system based on a set of input–outputs and is employed in different fields of engineering,.In the case of structural system identification, this can be done in the form of (a) Identifying structural parameters such as stiffness, vibration signatures such as frequencies, mode shapes, and damping ratios, and Cited by:   Structural Identification and Damage Detection using Genetic Algorithms Chan Ghee Koh and Michael John Perry, National University of Singapore, Singapore Vol. 6, .

Their combined citations are counted only for the first Substructural and progressive structural identification methods. CG Koh, B Hong, CY Liaw. Engineering structures 25 (12), Structural Identification and Damage Detection using Genetic Algorithms: Structures and Infrastructures Book Series, Vol. 6. CG Koh, MJ Perry. Crc. Damage detection via genetic algorithms Identification of structural parameters and damage characteristics based on the time domain matrix reconfiguration method Identification of structural damage location based on BP neural network and Dempster-Shafter evidence theory.

Whelan, M.J., Salas, N., and Kernicky, T. () “Structural Identification of a Tied Arch Bridge using Genetic Algorithms and Ambient Vibration Monitoring with a Wireless Sensor Network,” Journal of Civil Structural Health Monitoring, Vol. 8, No. 2,   Liszkai, T. R. "Application of an Implicit Redundant Genetic Algorithm for Structural Damage Identification of Flexible Structures." Proceedings of the ASME/JSME Pressure Vessels and Piping Conference. Experience With Creep-Strength Enhanced Ferritic Steels and New and Emerging Computational Methods. San Diego, California, : T. R. Liszkai.


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Structural identification and damage detection using genetic algorithms by Chan Ghee Koh Download PDF EPUB FB2

Structural Identification and Damage Detection using Genetic Algorithms: Structures and Infrastructures Book Series, Vol. 6 [Koh, Chan Ghee, Perry, Michael J.] on *FREE* shipping on qualifying offers.

Structural Identification and Damage Detection using Genetic Algorithms: Structures and Infrastructures Book SeriesAuthor: Chan Ghee Koh, Michael J. Perry. Structural Identification and Damage Detection using Genetic Algorithms book Structures and Infrastructures Book Series, Vol.

6 By Chan Ghee Koh, Michael J. PerryAuthor: Chan Ghee Koh, Michael J. Perry. This book is intended for researchers, engineers and graduate students in structural and mechanical engineering, particularly for those interested in model calibration, parameter estimation and damage detection of structural and mechanical systems using the state-of-the-art GA methodology.

Get this from a library. Structural identification and damage detection using genetic algorithms. [Chan Ghee Koh; M J Perry] -- "Rapid advances in computational methods and computer capabilities have led to a new generation of structural identification strategies.

Robust and efficient methods have successfully been developed. Structural Identification and Damage Detection using Genetic Algorithms: Structures and Infrastructures Book Series, Vol. 6 - CRC Press Book Rapid advances in computational methods and computer capabilities have led to a new generation of structural identification strategies.

Structural Identification and Damage Detection 3 Overview of Structural Identification Methods 3 2. A Primer to Genetic Algorithms 15 Background to GA 15 A Simple GA 17 Theoretical Framework 22 Advances in GAs 24 Chapter Summary 27 3.

An Improved GA Strategy 29 SSRM 30 iGAMAS 34 Chapter Summary 43 4. In this chapter, the latest developments by the authors in the area of structural identification and structural damage detection using genetic algorithms are : C.

Koh. Genetic algorithms explore the region of the whole solution space and can obtain the global optimum. In this paper, a genetic algorithm with real number encoding is applied to identify the structural damage by minimizing the objective function, which directly compares.

Structural damage detection consists of determining the location and severity of damage in civil structures by using measured parameters. Genetic algorithm is a meta-heuristic computing method for finding approximated global minimums in large optimization problems and has the advantage of Cited by: 7.

Genetic algorithms (GA) have proved to be a robust, efficient search technique for many problems. In this chapter, the latest developments by the authors in the area of structural identification and structural damage detection using genetic algorithms are presented.

A GA strategy involving a search Cited by: 2. This book is intended for researchers, engineers and graduate students in structural and mechanical engineering, particularly for those interested in model calibration, parameter estimation and damage detection of structural and mechanical systems using the state-of-the-art GA methodology.

It is the intention of this book, believed to be the first on this topic, to provide readers with the background and recent developments on GA-based methods for parameter identification, model updating and damage detection of structural dynamic systems.

Structural damage identification based on finite element (FE) model updating has been a research direction of increasing interest over the last decade in the mechanical, civil, aerospace, etc., engineering fields.

Various studies have addressed direct, sensitivity-based, probabilistic, statistical, and iterative methods for updating FE models for structural damage by:   The damage identification method developed using the implicit redundant genetic algorithm provides greater accuracy in identifying the location and severity of damage in all case studies even in the presence of noise.

In Fig.5 and 6, to discuss the possibility on the identification of small damage, we show the results identified by both filtering algorithms on the damaged grade with 5% at 1st and 3rd stories for original lateral horizontal line is the number of iterations and the vertical line means the non-dimensional value of the estimation of damaged grade and story based on eq.(18) and (21).

Amiri et al. [29] described a damage detection method based on defining the damage detection problem as an optimization problem by using genetic and pattern search algorithms in order to detect.

A one stage damage detection technique using spectral density analysis and parallel genetic algorithms. In Structural Health Monitoring: Research and Applications (Key Engineering Materials; Vol.

).Cited by: 1. Structural Identification and Damage Detection using Genetic Algorithms: Structures and Infrastructures Book Series, Vol. 6 1st Edition. Chan Ghee Koh, Michael J. Perry J Rapid advances in computational methods and computer capabilities have led to.

Identification of structural parameters based on PZT impedance using genetic algorithms. Hu, Y. Yang, L. Zhang, Y. Lu Although this method has been successfully applied for various engineering structures for damage detection, it is unable to specify the effect of damage on structural properties.

spring and damper components Cited by: 1. Advanced Structural Damage Detection: From Theory to Engineering Applications is written by academic experts in the field and provides students, engineers and other technical specialists with a comprehensive review of recent developments in various monitoring techniques and their applications to SHM.

Contributing to an area which is the subject Format: Hardcover. Genetic Algorithms (GA) are powerful tools for solving large and complicated optimization problems. Objective functions used in parameter estimation (PE) are commonly nonlinear due to available measurements at a limited number of degrees of freedom for a structure.

Sparse measurements create a fairly complicated objective function surface that requires a robust algorithm to find its global.Written by global leaders and pioneers in the field, this book is a must-have read for researchers, practicing engineers and university faculty working in SHM.

Structural Health Monitoring: A Machine Learning Perspective is the first comprehensive book on the general problem of structural health monitoring. The authors, renowned experts in the field, consider structural health monitoring in a.Our research team is primarily focusing on structural dynamics applications with emphasis on structural health monitoring, damage detection and vibration control of engineering structures.

Our research team members are world wide known experts in civil, mechanical, aerospace and electrical engineering. Our latest findings, updates, publications and benchmark data are shared here on this website.