Construction of Data-Driven Performance Digital Twin for a Real-World Gas Turbine Anomaly Detection Considering Uncertainty

Anomaly detection and failure prediction of gas turbines is of great importance for ensuring reliable operation. This work presents a novel approach for anomaly detection based on a data-driven performance digital twin of gas turbine engines. The developed digital twin consists of two parts: uncerta...

Descripción completa

Detalles Bibliográficos
Autores principales: Ma, Yangfeifei, Zhu, Xinyun, Lu, Jilong, Yang, Pan, Sun, Jianzhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422313/
https://www.ncbi.nlm.nih.gov/pubmed/37571444
http://dx.doi.org/10.3390/s23156660

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422313/
https://www.ncbi.nlm.nih.gov/pubmed/37571444
http://dx.doi.org/10.3390/s23156660

Ejemplares similares