Classification of damage signatures in composite plates using one-class SVMs

Santanu Das, Ashok N. Srivastava, Aditi Chattopadhyay

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Scopus citations


Damage characterization through wave propagation and scattering is of considerable interest to many non-destructive evaluation techniques. For fiber-reinforced composites, complex waves can be generated during the tests due to the non-homogeneous and anisotropic nature of the material when compared to isotropic materials. Additional complexities are introduced due to the presence of the damage and thus results in difficulty to characterize these defects. The inability to detect damage in composite structures limits their use in practice. A major task of structural health monitoring is to identify and characterize the existing defects or defect evolution through the interactions between structural features and multidisciplinary physical phenomena. In a wave-based approach to addressing this problem, the presence of damage is characterized by the changes in the signature of the resultant wave that propagates through the structure. In order to measure and characterize the wave propagation, we use the response of the surface-mounted piezoelectric transducers as input to an advanced machine-learning based classifier known as a Support Vector Machine.123

Original languageEnglish (US)
Title of host publication2007 IEEE Aerospace Conference Digest
StatePublished - 2007
Event2007 IEEE Aerospace Conference - Big Sky, MT, United States
Duration: Mar 3 2007Mar 10 2007

Publication series

NameIEEE Aerospace Conference Proceedings
ISSN (Print)1095-323X


Other2007 IEEE Aerospace Conference
Country/TerritoryUnited States
CityBig Sky, MT

ASJC Scopus subject areas

  • Aerospace Engineering
  • Space and Planetary Science


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