A Neural Network Symbolic Approach to Structural Health Monitoring in Aerospace Applications
Author:
Affiliation:
1. School of Aerospace Engineering, University of Rome “La Sapienza”,Rome,Italy,00138
2. University of Rome “La Sapienza”,Department of Information Engineering, Electronics and Telecommunications (DIET),Rome,Italy,00184
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10609966/10611750/10612130.pdf?arnumber=10612130
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1. Failure analysis of satellite subsystems to define suitable de-orbit devices
2. Machine Learning Techniques for Satellite Fault Diagnosis
3. A survey on Fault Detection, Isolation and Recovery (FDIR) module in satellite onboard software
4. Structural Health Monitoring: An Enabler for Responsive Satellites
5. Distributed Reservoir Computing with Sparse Readouts [Research Frontier]
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