4.4 Article

Evaluation of Delamination Damage on Composite Plates using an Artificial Neural Network for the Radiographic Image Analysis

Journal

JOURNAL OF COMPOSITE MATERIALS
Volume 44, Issue 9, Pages 1139-1159

Publisher

SAGE PUBLICATIONS LTD
DOI: 10.1177/0021998309351244

Keywords

drilling; image segmentation; image analysis; maximum thrust force; delamination factors; non-destructive testing

Funding

  1. Portuguese Fundacao para a Ciencia e a Tecnologia (FCT) [POSC/EEA-SRI/55386/2004, PTDC/EME-TME/66207/2006]
  2. Fundação para a Ciência e a Tecnologia [PTDC/EME-TME/66207/2006, POSC/EEA-SRI/55386/2004] Funding Source: FCT

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Drilling carbon/epoxy laminates is a common operation in manufacturing and assembly. However, it is necessary to adapt the drilling operations to the drilling tools correctly to avoid the high risk of delamination. Delamination can severely affect the mechanical properties of the parts produced. Production of high quality holes with minimal damage is a key challenge. In this article, delamination caused in laminate plates by drilling is evaluated from radiographic images. To accomplish this goal, a novel solution based on an artificial neural network is employed in the analysis of the radiographic images.

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