A one-class generative adversarial detection framework for multifunctional fault diagnoses
In this article, fault diagnosis is of great significance for system health maintenance. For real applications, diagnosis accuracy suffers from unbalanced data patterns, where normal data are usually abundant than anomaly ones, leading to tremendous diagnosis obstacles. Therefore, it is challenging...
| Autor principal: | |
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| Outros Autores: | , , |
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2022
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10400.1/17847 |
| País: | Portugal |
| Oai: | oai:sapientia.ualg.pt:10400.1/17847 |