Damage location in a stiffened composite panel using Lamb waves and neural networks

D. Chetwynd, F. Mustapha, K. Worden, J.A. Rongong, S.G. Pierce, J.M. Dulieu-Barton

Research output: Contribution to conferencePaper

1 Citation (Scopus)


Neural networks have proved to be very powerful tools in pattern recognition and machine learning and have consequently seen a great deal of applications in Structural Health Monitoring; a field where Pattern Recognition is one of the main lines of attack. The current paper presents a case study of damage detection and location in a stiffened composite panel interrogated by ultrasonic Lamb waves. Rather than work directly on features extracted from the wave profiles, the proposed approach derives secondary features in the form of a vector of novelty
indices for the plate. This can be used to train both neural network classifiers and regressors and the use of both for damage location is demonstrated in the paper.
Original languageEnglish
Number of pages9
Publication statusPublished - 2007
Event25th International Modal Analysis Conference - Orlando, United States
Duration: 19 Feb 200722 Feb 2007


Conference25th International Modal Analysis Conference
Abbreviated titleIMAC XXV
Country/TerritoryUnited States


  • composite materials
  • lamb waves
  • neural networks


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