In this paper, we replicate the dynamics of an earthquake in a laboratory experiment by employing an optical scrambler and a polarimeter. This experimental setup emulates the impact of a real earthquake-induced ground displacement values on the state of polarization of light propagating through an optical fiber, modeled using a Waveplate computer-based approach. A large dataset of polarization evolution was collected from the experiment to evaluate the performance of our pre-trained machine learning model in detecting the primary earthquake wave which precedes the destructive wave by tens of seconds. The objective is to perform a comparative analysis with our previous findings which were conducted using the same machine learning model, but applied to computer-based simulations of the Waveplate model. The results demonstrate that the model achieved over 95% of accuracy in both computer-based simulations and Laboratory-based experiment, validating the high accuracy and reliability of our system in early earthquake detection despite the inherent challenges of experimental errors

Experimental earthquake early detection through polarization changes in intelligent optical networks

Awad, Hasan;Straullu, Stefano;Usmani, Fehmida;Virgillito, Emanuele;Proietti, Roberto;Curri, Vittorio
2025

Abstract

In this paper, we replicate the dynamics of an earthquake in a laboratory experiment by employing an optical scrambler and a polarimeter. This experimental setup emulates the impact of a real earthquake-induced ground displacement values on the state of polarization of light propagating through an optical fiber, modeled using a Waveplate computer-based approach. A large dataset of polarization evolution was collected from the experiment to evaluate the performance of our pre-trained machine learning model in detecting the primary earthquake wave which precedes the destructive wave by tens of seconds. The objective is to perform a comparative analysis with our previous findings which were conducted using the same machine learning model, but applied to computer-based simulations of the Waveplate model. The results demonstrate that the model achieved over 95% of accuracy in both computer-based simulations and Laboratory-based experiment, validating the high accuracy and reliability of our system in early earthquake detection despite the inherent challenges of experimental errors
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3002531