Transformer-Based Prognostics: Enhancing Network Availability by Improved Monitoring of Optical Fiber Amplifiers
Dominic Schneider, Lutz Rapp, Christoph Ament
TL;DR
This paper introduces a lightweight transformer model that predicts optical fiber amplifier lifetime from monitoring data, improving network reliability through real-time, edge-level predictive maintenance for autonomous operation.
Contribution
The paper presents a novel transformer-based approach for optical amplifier prognosis, enabling real-time predictive maintenance at the edge in optical networks.
Findings
The model accurately predicts amplifier lifetime from monitoring data.
Real-time predictions facilitate proactive maintenance and reduce network downtime.
The approach enhances network availability and reliability.
Abstract
We enhance optical network availability and reliability through a lightweight transformer model that predicts optical fiber amplifier lifetime from condition-based monitoring data, enabling real-time, edge-level predictive maintenance and advancing deployable AI for autonomous network operation.
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