Acoustic signal analysis
Audio-based classification for fluid mechanics and non-destructive testing
Automatic characterization of physical events from their acoustic signature, combining traditional signal processing with machine learning.
Topics:
- Water-drop impact characterization from audio recordings (fluid-mechanics applications) in collaboration with Dr. Merav Arogeti and Dr. Etan Fisher.
- Non-destructive testing of metal components via multiple-tapping acoustics in collaboration with Dr. Oshrit Hoffer.
Representative publications:
- M. Arogeti, E. Fisher and D. Bykhovsky, “Automatic Classification of Water Drop Impact Characteristics Using Audio Information,” Results in Engineering, vol. 26, p. 103562, Jun. 2025. doi:10.1016/j.rineng.2024.103562
- D. Bykhovsky et al., “Multiple Tapping Method for Non-Destructive Testing of Defects in Metal Components,” Measurement, vol. 270, p. 115582, 2026. doi:10.1016/j.measurement.2026.120751
- M. Arogeti, E. Fisher and D. Bykhovsky, “Sound Analysis of Drop Characteristics by Evaluation of Impact on Water Pool,” Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), Poznan, Poland, Sep. 2024, pp. 144–148.
- S. Marciano, A. Duek, M. Arogeti, E. Fisher, D. Rina Elbaz, K. Panfilov, S. Demin, D. Bykhovsky, “Enhanced Audio-Based Analysis of Drop Characteristics by Evaluation of Impact on Water Pool,” IEEE USBEREIT, Ekaterinburg, Russia, May 2025. doi:10.1109/USBEREIT65494.2025.11054227