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Enhanced defect detection aided by robotics

AutoDISC: Enhanced defect detection aided by CAD controlled robotics


Future generation aircraft will consist mostly of carbon composite materials. The modes of failure in composite intensive aircraft are not fully known as they are still near the beginning of their design life, although they are susceptible to internal impact damage, not visible at the surface. Current non-destructive inspection (NDI) of composites in production and service is still largely manual with low area coverage and images difficult to interpret because of macroscopic structural anisotropy.

AutoDISK Project


To address these problems the project proposes two key NDI innovations:

  • Up to 100% volume NDI coverage using gantry deployed, CAD controlled robotics so that inspection records at any point can be accurately compared at successive maintenance downtime intervals; this allows health diagnostics and prognostics.
  • A step increase in current detection probability for composite defects. This is implemented through an inference engine performing similarity analysis on spatial and temporal changes in images, with coherent noise removal performed by advanced signal processing.

Project Partners

  • Plant Integrity Ltd
  • Jackweld
  • NetComposites
  • InnoTec UK
  • KCC
  • Brunel University London

For more information, please visit the AutoDISC website


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Project last modified 11/03/2021