Ultrasound Insight: Using Entropy and Signal Energy to Classify 3D-Printed High-Performance Plastics

Industry: The study is focused on the additive manufacturing industry, specifically on the use of
high-performance thermoplastics like polyetherketoneketone (PEKK) in 3D printing. PEKK
components are valued in aerospace, industrial, and medical applications for their ability to
withstand high temperatures, resist chemicals, and bear significant mechanical loads.

Challenge: A critical challenge in using 3D-printed PEKK components is determining their
crystallinity. Annealing these components can enhance their structural stability and thermal
resistance but distinguishing between annealed (high crystallinity) and unannealed (low
crystallinity) components non-destructively and rapidly is difficult with current methods.

Extraordinary Aspects of the Paper: The study’s novelty lies in its application of entropy-
based signal processing techniques to ultrasound data for material classification. Unlike
traditional energy-based methods, which proved ineffective, the use of joint entropy and a
limiting form of Renyi’s entropy successfully identified the microstructural differences between
annealed and unannealed PEKK components. This approach offers a non-destructive, rapid,
and reliable method for assessing the quality of 3D-printed high-performance polymers, with
potential to significantly enhance manufacturing processes and material optimization in various
high-tech industries.

Note: The quick summaries in this section focus on how GaGe Digitizer products have helped solve advanced problems.  Paraphrased using simplified terminology, the summaries are intended to make the achievements understandable to people from a variety of backgrounds.  Please use the provided link to source the original paper for technical clarity.