A Weakly Supervised Gas-Path Anomaly Detection Method for Civil Aero-Engines Based on Mapping Relationship Mining of Gas-Path Parameters and Improved Density Peak Clustering

Gas-path anomalies account for more than 90% of all civil aero-engine anomalies. It is essential to develop accurate gas-path anomaly detection methods. Therefore, a weakly supervised gas-path anomaly detection method for civil aero-engines based on mapping relationship mining of gas-path parameters...

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Detalles Bibliográficos
Autores principales: Sun, Hao, Fu, Xuyun, Zhong, Shisheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271765/
https://www.ncbi.nlm.nih.gov/pubmed/34282788
http://dx.doi.org/10.3390/s21134526

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271765/
https://www.ncbi.nlm.nih.gov/pubmed/34282788
http://dx.doi.org/10.3390/s21134526

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