Joint Sensing of Two Independent Failures in Optical Network Using a Single Variational Auto-Encoder Model

We conducted unsupervised learning of two independent failures including optical fiber bending and ROADM optical filter shift using a VAE model. We successfully detected these anomalies with sufficient high accuracy of over 90%.

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Publication Details

Published
2025-06-29
DOI
https://doi.org/10.23919/oecc/psc62146.2025.11111355
Primary Topic
Fault Detection and Control Systems
Type
article
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article

Joint Sensing of Two Independent Failures in Optical Network Using a Single Variational Auto-Encoder Model

Yoshinari Awaji, Akira Hirano, Sugang Xu, Yukiko Yamamoto
Fault Detection and Control Systems
article

Joint Sensing of Two Independent Failures in Optical Network Using a Single Variational Auto-Encoder Model

Yoshinari Awaji, Akira Hirano, Sugang Xu, Yukiko Yamamoto
article en

Abstract

We conducted unsupervised learning of two independent failures including optical fiber bending and ROADM optical filter shift using a VAE model. We successfully detected these anomalies with sufficient high accuracy of over 90%.

Tokyo Denki University (JP), National Institute of Information and Communications Technology (JP)
Openalex Percentile: Top 75%
Fault Detection and Control Systems
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