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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.

Keywords

Fuzzy Logic Damage Detection Structural Health Monitoring Lamb Wave General Regression Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.College of EngineeringShri Vithal Education and Research InstitutePandharpurIndia
  2. 2.Department of Aerospace EngineeringIndian Institute of ScienceBangaloreIndia

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