Analysis of Deep Learning-Based Frameworks for Fault Detection in Big Research Infrastructures: A Case Study of the SOLARIS Synchrotron

Analysis of Deep Learning-Based Frameworks for Fault Detection in Big Research Infrastructures: A Case Study of the SOLARIS Synchrotron

This paper presents an in-depth analysis of multi-modal, deep learning-based frameworks for fault detection within big research infrastructures, with a specific focus on synchrotron facilities. The study investigates various approaches and architectures and their accuracy in identifying anomalies in...

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Bibliographic Details
Main Authors: Michal Piekarski, Joanna Jaworek-Korjakowska, Adriana Izabela Wawrzyniak
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Anomaly detection
convolutional neural networks
signal analysis
synchrotron radiation system
transfer learning
Online Access:https://ieeexplore.ieee.org/document/10781315/
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https://ieeexplore.ieee.org/document/10781315/

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