[4A4] Deploying non-linear resonance: a self-referencing NDT method for rapid assessment of metal components

Daniel Rodriguez Sanmartin, Alex Brennan and Julian Wright
Theta Technologies Ltd, UK 

Closed defects such as cracks in metals or delaminations and kissing bonds in composites represent a common problem for well-established manufacturing methods, such as subtractive CNC machining, and novel methods such as additive manufacturing (AM).

These defects may be difficult to detect using traditional NDT methods, or may require characterisation techniques, such as X-ray CT, which are not suitable for production environments due to high costs and protracted inspection times. Moreover, several processing steps, each increasing component cost, may need to be completed before the non-destructive evaluation is even possible. Therefore, there is a general industry need for an NDT method capable of rapid assessment of components at different manufacturing stages.

For example, one of the technical challenges present in metals AM is solidification cracking, where the interior of the grains solidify before the grain boundaries. This can produce voids upon cooling eventually leading to cracking of the structure, which could then propagate during thermal treatment used for stress relieving or while the part is in service, eventually leading to a component failure.

Non Linear Resonance (NLR) is a cost effective characterisation technique capable of providing a go/no-go rapid assessment of components. NLR has the advantage, over other linear resonance-based methods, of being a self-referencing technique, therefore it is capable of exposing defects at early stages of manufacture without the need for a “known good” reference sample. We are now working with industry partners to deploy NLR at different stages of metal manufacturing processes, including testing of bar stock, structures used for validation of built parts in AM, to the testing of components after they have been post-processed.

The presentation will give examples of completed NLR systems and provide a summary of data collected for a variety of samples demonstrating the capability of the technique.