Summary
Protecting critical power infrastructure requires reliable detection of activities that threaten cables in urban and submarine environments. Distributed acoustic sensing (DAS) enables continuous monitoring by capturing vibrations along the cable route. In this work, we analyze signal characteristics for activities that can lead to cable damage, including excavator digging, jackhammering, auger drilling, and diver interference. Based on this analysis, we present a detection framework that combines deep learning and signal processing to enhance adaptability and robustness.
Read more Read lessThe system is evaluated through real-world tests, demonstrating high detection accuracy for critical threats: perfect detection of excavator digging and jackhammering, partial detection of auger drilling, and successful identification of diver interference and mechanically induced seabed disturbances in submarine conditions. Additionally, we propose a secure data-sharing architecture that enables fast and trustworthy exchange of measurements and ground truth information, accelerating model retraining while adhering to cybersecurity standards. These results confirm the feasibility and effectiveness of DAS-based monitoring for improving cable protection and resilience.
Additional informations
| Publication type | Session Materials |
|---|---|
| Reference | B1_12445_2026 |
| Publication year | |
| Publisher | CIGRE |
| Country | Germany |
| Study committees | |
| File size | 1 MB |
| Price for non member | 30 € |
| Price for member | 30 € |
Authors
SFAR ZAOUI Wissem - AP Sensing GmbH, Germany; AGHANOURIAN Negar - AP Sensing GmbH, Germany; DRAPP Bernd - AP Sensing GmbH, Germany; MOCKENHAUPT Daniel - AP Sensing GmbH, Germany; STROHBACH Martin - AP Sensing GmbH, Germany; SYED Saiffuddin - AP Sensing GmbH, Germany; AINHIRN Florian - Wiener Netze GmbH, Austria
Keywords
