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

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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Bibliographic Details
Main Authors:	Xiaoguang Zhang, Xuanhao Hua, Junjie Zhu, Meng Ma
Format:	Article
Language:	English
Published:	MDPI AG 2023-06-01
Series:	Sensors
Subjects:	interpretable bidirectional LSTM data fusion fault simulation
Online Access:	https://www.mdpi.com/1424-8220/23/12/5636

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