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Introduction

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Structural Health Monitoring Using Genetic Fuzzy Systems

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Abstract

Chapter 1 defines the various terms and definitions related to structural health monitoring. The main technical approaches used for structural health monitoring are discussed. These include methods based on mathematical models of the undamaged and damaged structures and those based on modal data such as frequencies and mode shapes. In addition, localized damage detection methods based on strain monitoring and non-destructive testing are described. Three main soft computing methods (neural networks, genetic algorithms, and fuzzy logic) used for solving the structural health monitoring problem are discussed with reference to the published literature. The advantages and shortcomings of each of these methods are brought out, and techniques which hybridize these methods are shown to be good alternatives. The genetic fuzzy system is introduced as an excellent choice for solving the pattern recognition problems in structural health monitoring. The helicopter rotor system health and usage monitoring system is used as an example to illustrate the different ideas for a real engineering system. The chapter ends with a summary of the book.

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Authors and Affiliations

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

    Prashant M. Pawar

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

    Ranjan Ganguli

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  1. Prashant M. Pawar
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  2. Ranjan Ganguli
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Correspondence to Prashant M. Pawar .

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© 2011 Springer-Verlag London Limited

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Pawar, P.M., Ganguli, R. (2011). Introduction. In: Structural Health Monitoring Using Genetic Fuzzy Systems. Springer, London. https://doi.org/10.1007/978-0-85729-907-9_1

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  • DOI: https://doi.org/10.1007/978-0-85729-907-9_1

  • Publisher Name: Springer, London

  • Print ISBN: 978-0-85729-906-2

  • Online ISBN: 978-0-85729-907-9

  • eBook Packages: EngineeringEngineering (R0)

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