Intelligent Fault Diagnosis of Liquid Rocket Engine via Interpretable LSTM with Multisensory Data

Fault diagnosis is essential for high energy systems such as liquid rocket engines (LREs) due to harsh thermal and mechanical working environment. In this study, a novel method based on one-dimension Convolutional Neural Network (1D-CNN) and interpretable bidirectional Long Short-term Memory (LSTM)...

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Detalles Bibliográficos
Autores principales: Zhang, Xiaoguang, Hua, Xuanhao, Zhu, Junjie, Ma, Meng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303355/
https://www.ncbi.nlm.nih.gov/pubmed/37420802
http://dx.doi.org/10.3390/s23125636

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303355/
https://www.ncbi.nlm.nih.gov/pubmed/37420802
http://dx.doi.org/10.3390/s23125636

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