A real-time fault diagnosis method for hypersonic air vehicle with sensor fault based on the auto temporal convolutional network
- 18 November 2021
- journal article
- research article
- Published by Elsevier BV in Aerospace Science and Technology
- Vol. 119, 107220
- https://doi.org/10.1016/j.ast.2021.107220
Abstract
No abstract availableKeywords
This publication has 29 references indexed in Scilit:
- GNASPublished by Association for Computing Machinery (ACM) ,2018
- Artificial intelligence for fault diagnosis of rotating machinery: A reviewMechanical Systems and Signal Processing, 2018
- t-SNE Visualization of Large-Scale Neural RecordingsNeural Computation, 2018
- A Novel Fault Diagnosis Method Based on Integrating Empirical Wavelet Transform and Fuzzy Entropy for Motor BearingIEEE Access, 2018
- SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year AnniversaryJournal of Artificial Intelligence Research, 2018
- Performance assessment of multi-stage thermoelectric generators on hypersonic vehicles at a large temperature differenceApplied Thermal Engineering, 2018
- Prediction of bending force in the hot strip rolling process using artificial neural network and genetic algorithm (ANN-GA)The International Journal of Advanced Manufacturing Technology, 2017
- LSTM: A Search Space OdysseyIEEE Transactions on Neural Networks and Learning Systems, 2016
- Spectral kurtosis for fault detection, diagnosis and prognostics of rotating machines: A review with applicationsMechanical Systems and Signal Processing, 2016
- An Asynchronous Multithreaded Algorithm for the Maximum Network Flow Problem with Nonblocking Global Relabeling HeuristicIEEE Transactions on Parallel and Distributed Systems, 2010