D7.2 - Arc Welding Process Monitoring Using Neural Networks and Audio Signal Analysis
- Event
- SMSI 2023
2023-05-08 - 2023-05-11
Nürnberg - Band
- Lectures
- Chapter
- D7 - Al Approches in Measurement
- Author(s)
- S. Gourishetti, S. Grollmisch, J. Chauhan - Fraunhofer IDMT, Ilmenau (Germany), J. Bergmann, J. Hildebrand, M. Rohe, M. Sennewald - Technische Universität Ilmenau, Ilmenau (Germany)
- Pages
- 249 - 250
- DOI
- 10.5162/SMSI2023/D7.2
- ISBN
- 978-3-9819376-8-8
- Price
- free
Abstract
This paper investigates the potential of airborne sound analysis in the human hearing range for automatic defect classification in the arc welding process. We propose a novel sensor setup using microphones and perform several recording sessions under different process conditions. The proposed quality monitoring method using convolutional neural networks achieves 80.5% accuracy in detecting deviations in the arc welding process. This confirms the suitability of airborne analysis and leaves room for improvement in future work.