2023
Lykourinas, Antonios; Skodras, Athanassios
Real-time ENF monitoring with a Raspberry Pi 3 Model B Technical Report
2023.
Abstract | Links | BibTeX | Tags: ENF, Hilbert, Power Grid Frequency Analysis, Raspberry Pi
@techreport{Lykourinas2023_1,
title = {Real-time ENF monitoring with a Raspberry Pi 3 Model B},
author = {Antonios Lykourinas and Athanassios Skodras},
url = {http://dsip.ece.upatras.gr/wp-content/uploads/2023/06/DSIP-TR002-29.05.2023.pdf},
year = {2023},
date = {2023-05-29},
urldate = {2023-05-29},
abstract = {Electrical Network Frequency (ENF), the instantaneous fluctuation of the power grid’s frequency around its nominal frequency due to the imbalance between energy production and consumption, was initially used in forensics applications and since then it has been adopted into a wide range of applications. In this report, the development of a real-time ENF monitoring system is described. The whole system is based on a Raspberry Pi Model B computer, which performs the filtering of the digital signal, the calculation of the ENF values and finally the storage of the frequency values in real-time. Signal capturing is achieved by means of a sensing circuit that we have also designed and constructed. The performance of the system has been compared to existing solutions, thus validating its measuring accuracy},
keywords = {ENF, Hilbert, Power Grid Frequency Analysis, Raspberry Pi},
pubstate = {published},
tppubtype = {techreport}
}
Electrical Network Frequency (ENF), the instantaneous fluctuation of the power grid’s frequency around its nominal frequency due to the imbalance between energy production and consumption, was initially used in forensics applications and since then it has been adopted into a wide range of applications. In this report, the development of a real-time ENF monitoring system is described. The whole system is based on a Raspberry Pi Model B computer, which performs the filtering of the digital signal, the calculation of the ENF values and finally the storage of the frequency values in real-time. Signal capturing is achieved by means of a sensing circuit that we have also designed and constructed. The performance of the system has been compared to existing solutions, thus validating its measuring accuracy