Multi-module-based CVAE to predict HVCM faults in the SNS accelerator

Multi-module-based CVAE to predict HVCM faults in the SNS accelerator

We present a multi-module framework based on Conditional Variational Autoencoder (CVAE) to detect anomalies in the power signals coming from multiple High Voltage Converter Modulators (HVCMs). We condition the model with the specific modulator type to capture different representations of the normalw...

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Detalhes bibliográficos
Principais autores: Yasir Alanazi, Malachi Schram, Kishansingh Rajput, Steven Goldenberg, Lasitha Vidyaratne, Chris Pappas, Majdi I. Radaideh, Dan Lu, Pradeep Ramuhalli, Sarah Cousineau
Formato: Artigo
Idioma:English
Publicado em: Elsevier 2023-09-01
coleção:Machine Learning with Applications
Assuntos:
Anomaly detection
Variational Autoencoder
Spallation Neutron Source
Accelerators
High Voltage Converter Modulator
Acesso em linha:http://www.sciencedirect.com/science/article/pii/S2666827023000373

Internet

http://www.sciencedirect.com/science/article/pii/S2666827023000373

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