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Structural Health Monitoring Using Genetic Fuzzy Systems

  • Book
  • © 2011

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Authors:
  1. Prashant M. Pawar

    1. College of Engineering, Shri Vithal Education and Research Inst., Pandharpur, India

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  2. Ranjan Ganguli

    1. Department of Aerospace Engineering, Indian Institute of Science, Bangalore, India

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    You can also search for this author in PubMed   Google Scholar

  • Demonstrates the application of genetic fuzzy systems to engineering problems, which will be of interest to computer scientists and applied mathematicians

  • Provides the reader with information on the use of genetic fuzzy systems as a computational tool for solving structural health monitoring problems

  • Examples provided in this book assist the reader in developing genetic fuzzy systems for new structures and aerospace systems

  • Includes supplementary material: sn.pub/extras

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Table of contents (5 chapters)

  1. Front Matter

    Pages I-VIII
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  2. Introduction

    • Prashant M. Pawar, Ranjan Ganguli
    Pages 1-23

  3. Genetic Fuzzy System

    • Prashant M. Pawar, Ranjan Ganguli
    Pages 25-40

  4. Structural Health Monitoring of Beams

    • Prashant M. Pawar, Ranjan Ganguli
    Pages 41-66

  5. Structural Health Monitoring of Composite Tubes

    • Prashant M. Pawar, Ranjan Ganguli
    Pages 67-83

  6. Structural Health Monitoring of Composite Helicopter Rotor

    • Prashant M. Pawar, Ranjan Ganguli
    Pages 85-125

  7. Back Matter

    Pages 127-130
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Keywords

About this book

Structural health monitoring (SHM) has emerged as a prominent research area in recent years owing to increasing concerns about structural safety, and the need to monitor and extend the lives of existing structures. Structural Health Monitoring Using Genetic Fuzzy Systems elaborates the process of intelligent SHM development and implementation using the evolutionary system. The use of a genetic algorithm automates the development of the fuzzy system, and makes the method easy to use for problems involving a large number of measurements, damage locations and sizes; such problems being typical of SHM. The ideas behind fuzzy logic, genetic algorithms and genetic fuzzy systems are also explained. The functionality of the genetic fuzzy system architecture is elucidated within a case-study framework, covering: • SHM of beams; • SHM of composite tubes; and • SHM of helicopter rotor blades. Structural Health Monitoring Using Genetic Fuzzy Systems will be useful for aerospace, civil and mechanical engineers working with structures and structured components. It will also be useful for computer scientists and applied mathematicians interested in the application of genetic fuzzy systems to engineering problems.

Authors and Affiliations

  • College of Engineering, Shri Vithal Education and Research Inst., Pandharpur, India

    Prashant M. Pawar

  • Department of Aerospace Engineering, Indian Institute of Science, Bangalore, India

    Ranjan Ganguli

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