A State-Supervised Model and Novel Anomaly Index for Gas Turbines Blade Fault Detection Under Multi-Operating Conditions
To meet industrial demands, gas turbines typically operate under multiple conditions, presenting unique challenges for fault diagnosis. This paper proposes a novel blade fault detection framework designed for such environments. First, a State-Supervised Variational Autoencoder (SS-VAE) model is intr...
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| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10843193/ |
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