2025 SMSI Bannerklein

P3.11 Plastic Material Classification using Neural Network based Audio Signal Analysis

Event
SMSI 2020
-
(did not take place because of Covid-19 virus pandemic)
Band
SMSI 2020 - Measurement Science
Chapter
P3 Advanced Methods and Approaches in Measurement
Author(s)
S. Grollmisch - University of Technology, Ilmenau (Germany), D. Johnson, T. Krüger, J. Liebetrau - Fraunhofer Institute IDMT, Ilmenau (Germany)
Pages
337 - 338
DOI
10.5162/SMSI2020/P3.11
ISBN
978-3-9819376-2-6
Price
free

Abstract

Analyzing the acoustic response of products being struck is a potential method to detect material deviations or faults for automated quality control. To evaluate this, we implement a material detection system by equipping an air hockey table with two microphones and plastic pucks 3D printed using different materials. Using this setup, a dataset of the acoustic response of impacts on plastic materials was developed and published. A convolutional neural network trained on this data, achieved high classification accuracy even under noisy conditions demonstrating the potential of this approach.

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