Engineers at Swinburne University of Technology  have developed an inspection system based on artificial intelligence (AI) to detect and characterise internal flaws in composite materials in aircraft.

 

The technology has the potential to increase aeronautical safety and speed up component safety checks.

 

Aircraft made mostly from composite materials such as carbon-fibre-reinforced polymers are already on the drawing boards of major aeronautical manufacturers, which seek lighter planes able to carry more passengers, cargo and fuel.

 

While these ultralight materials are currently available, their widespread use is problematic because the process of scanning for potential flaws is expensive, time-consuming and gives less confidence than similar processes used for checking and certifying metals.

 

Swinburne researchers are tackling this challenge by developing an automated approach to processing data from scans of composite materials.

 

The goal is a process based on AI technology that enables analysis to be carried out with much greater speed and accuracy than a human technician could achieve.

 

The project is being led by the Defence Materials Technology Centre (DMTC), in collaboration with Swinburne, industry partner GKN Aerospace, and technical collaborator the Defence Science Technology Organisation (DSTO).

 

"There is a lot of pressure on the technicians who analyse the scans of composite materials for certification," said Dr Mark Hodge, CEO of the DMTC, based at Swinburne's Hawthorn campus.

 

"Getting it wrong could cost lives and a lot of money. The risk of those consequences means there is a tendency for the technician to be conservative and not certify parts that have any potentially threatening flaw."

 

Defects can be introduced into a composite material during manufacture or while the plane is in service. The difficulty in detecting these is one reason why composite parts are currently used only on non-load-bearing aircraft parts such as aerolons (the flaps that descend from the wing to control side-to-side movement), and even then only after a rigorous and time-consuming certification process.

 

Interiors of composite panels are currently examined using non-destructive inspection technologies, such as ultrasound. The panel is scanned with an ultrasonic probe attached to a robot that sends raw data displayed as squiggles akin to those produced by an electrocardiogram.

 

Only a handful of people in Australia are experienced enough to read the data at this level and to sign off on component safety. It can take a day to scan and assess one wing panel of just two square metres and interpretation is subjective, so an automated, objective process is needed.

 

"The AI inspection system developed at Swinburne mimics human intelligence to examine a sensor signal and draw out valuable information," said Professor Romesh Nagarajah who leads the Robotics and Non-Contact Inspection research team at Swinburne. "The signal information can then lead to the identification of any defects existing in the component."

 

Human inspection catalogues only two properties: irregular echoes in the signal and where those echoes occur, but the automated method is able to go into much more detail, much faster.

 

There are many benefits to this AI-based inspection system. Without any specialist support, it can be instructed to look for new types of defects. It also stores the data from each scan by date, a necessary tool when adhering to the aerospace industry's long audit trails.

 

Because of the stringent quality assurance requirements of aeronautical engineering, a technician will still be required to sign off on the inspection results provided by the ‘smart' inspection system.

 

Now that this stage of development is complete, the next step is for software coding engineers to refine the system for commercial use.