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Use of Soft Computing Tools for Damage Detection

In: Computational Techniques for Structural Health Monitoring

Author

Listed:
  • Srinivasan Gopalakrishnan

    (Indian Institute of Science)

  • Massimo Ruzzene

    (Georgia Institute of Technology)

  • Sathyanarayana Hanagud

    (Georgia Institute of Technology)

Abstract

This chapter gives an overview on the use of soft computing tools for damage detection in SHM. Here, two important soft computing tools, namely the genetic algorithms and the artificial neural network are addressed in regard to damage detection. Implementation of these methods under spectral finite element environment is discussed. The chapter first gives basic introduction to these methods and outlines the procedure for adaptation under spectral FEM environment. A number of examples are given to show the effectiveness of these methods for damage detection.

Suggested Citation

  • Srinivasan Gopalakrishnan & Massimo Ruzzene & Sathyanarayana Hanagud, 2011. "Use of Soft Computing Tools for Damage Detection," Springer Series in Reliability Engineering, in: Computational Techniques for Structural Health Monitoring, chapter 0, pages 463-493, Springer.
    • Handle: RePEc:spr:ssrchp:978-0-85729-284-1_11
    DOI: 10.1007/978-0-85729-284-1_11
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