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  4. Plastic Material Classification using Neural Network based Audio Signal Analysis
 
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2020
Conference Paper
Title

Plastic Material Classification using Neural Network based Audio Signal Analysis

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.
Author(s)
Grollmisch, Sascha  
Johnson, David
Krüger, Tobias  
Liebetrau, Judith  
Mainwork
SMSI 2020 - Sensor and Measurement Science International  
Conference
Conference "Sensor and Measurement Science International" (SMSI) 2020  
DOI
10.5162/SMSI2020/P3.11
Language
English
Fraunhofer-Institut für Digitale Medientechnologie IDMT  
Keyword(s)
  • Analyse Industriegeräusche

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