Enhanced Detection and Monitoring of Unauthorized Activities in High-Voltage Power Grids Using Distributed Acoustic Sensing (DAS) in Turkish Transmission Grid

Abstract This study presents the implementation and evaluation of a fiber-optic Distributed Acoustic Sensing (DAS) system for monitoring overhead high-voltage transmission lines in the Turkish Transmission Grid. The DAS system, deployed on a 154-kV transmission line spanning 40 km, utilizes existing optical ground wires (OPGW) for real-time acoustic and vibrational sensing. The study outlines the fundamental principles of DAS technology, detailing how optical fiber functions as a distributed sensor to detect mechanical disturbances along the transmission line. Signal processing algorithms and feature extraction techniques were developed to analyze recorded acoustic signatures associated with different types of activities, including structural impacts, mechanical tampering, and environmental stressors such as wind-induced vibrations and icing effects. Key signal features, including root mean square (RMS) amplitude, crest factor, zero-crossing rate, spectral centroid, power spectral density (PSD), and wavelet entropy, were extracted and analyzed for their suitability in activity classification. Extensive field tests were conducted, including controlled experiments such as hammering, mechanical and manual unscrewing, and metal cutting at various distances from the interrogation unit. A signal processing pipeline was implemented to enhance detection accuracy, utilizing noise reduction, spectral analysis, and feature-based classification. The developed detection algorithm processes real-time acoustic data and assigns an activity score based on extracted features, enabling efficient identification of anomalies and security threats along the transmission line. The system demonstrated high sensitivity to impulsive events, reliably detecting 22 out of 23 activities with a near-zero false alarm rate. The results indicate that DAS technology is capable of accurately monitoring and detecting unauthorized activities around high-voltage transmission towers and it can serve as an effective non-intrusive monitoring solution for power transmission infrastructure. The DAS technology presented herein has the potential to become an essential tool in ensuring the safety and reliability of Türkiye’s energy infrastructure, enabling rapid response to both human-made and natural threats.

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Publication Details

Journal
B&H eletrical engineering
Published
2026-01-14
DOI
https://doi.org/10.2478/bhee-2026-0009
Primary Topic
Thermal Analysis in Power Transmission
Type
article
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article

Enhanced Detection and Monitoring of Unauthorized Activities in High-Voltage Power Grids Using Distributed Acoustic Sensing (DAS) in Turkish Transmission Grid

Faruk Uyar, Mete Uzar, Ekmel Özbay, Barış İyidir et al.
B&H eletrical engineering
Thermal Analysis in Power Transmission
article

Enhanced Detection and Monitoring of Unauthorized Activities in High-Voltage Power Grids Using Distributed Acoustic Sensing (DAS) in Turkish Transmission Grid

Faruk Uyar, Mete Uzar, Ekmel Özbay, Barış İyidir, Ceyhun Cengiz, Ümit Aktaş
article en

Abstract

Abstract This study presents the implementation and evaluation of a fiber-optic Distributed Acoustic Sensing (DAS) system for monitoring overhead high-voltage transmission lines in the Turkish Transmission Grid. The DAS system, deployed on a 154-kV transmission line spanning 40 km, utilizes existing optical ground wires (OPGW) for real-time acoustic and vibrational sensing. The study outlines the fundamental principles of DAS technology, detailing how optical fiber functions as a distributed sensor to detect mechanical disturbances along the transmission line. Signal processing algorithms and feature extraction techniques were developed to analyze recorded acoustic signatures associated with different types of activities, including structural impacts, mechanical tampering, and environmental stressors such as wind-induced vibrations and icing effects. Key signal features, including root mean square (RMS) amplitude, crest factor, zero-crossing rate, spectral centroid, power spectral density (PSD), and wavelet entropy, were extracted and analyzed for their suitability in activity classification. Extensive field tests were conducted, including controlled experiments such as hammering, mechanical and manual unscrewing, and metal cutting at various distances from the interrogation unit. A signal processing pipeline was implemented to enhance detection accuracy, utilizing noise reduction, spectral analysis, and feature-based classification. The developed detection algorithm processes real-time acoustic data and assigns an activity score based on extracted features, enabling efficient identification of anomalies and security threats along the transmission line. The system demonstrated high sensitivity to impulsive events, reliably detecting 22 out of 23 activities with a near-zero false alarm rate. The results indicate that DAS technology is capable of accurately monitoring and detecting unauthorized activities around high-voltage transmission towers and it can serve as an effective non-intrusive monitoring solution for power transmission infrastructure. The DAS technology presented herein has the potential to become an essential tool in ensuring the safety and reliability of Türkiye’s energy infrastructure, enabling rapid response to both human-made and natural threats.

B&H eletrical engineering
Bilkent University (TR), Turkish Aerospace Industries (Turkey) (TR)
Industry, innovation and infrastructure
Openalex Percentile: Top 87%
Thermal Analysis in Power Transmission
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