AutoDISC: Enhanced defect detection aided by CAD controlled robotics
Background
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.
Objectives
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
Meet the Principal Investigator(s) for the project
Related Research Group(s)
Brunel Innovation Centre - A world-class research and technology centre that sits between the knowledge base and industry.
Partnering with confidence
Organisations interested in our research can partner with us with confidence backed by an external and independent benchmark: The Knowledge Exchange Framework. Read more.
Project last modified 11/03/2021