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- W2771677500 abstract "This paper addresses real-time structural health assessment as a form of aircraft selfawareness. Limited time and resources available on-board and incomplete measured data affected by uncertainty are the key challenges to face. We discuss a data-driven methodology that combines Multi-Step Reduced Order Modeling to support structural self-awareness, and unsupervised learning (Self-Organizing Maps) to identify optimal sets of sensor locations. In particular, two implementations of our sensor placement strategy are presented and compared for a composite wing panel subjected to a number of damage conditions." @default.
- W2771677500 created "2017-12-22" @default.
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- W2771677500 date "2017-09-28" @default.
- W2771677500 modified "2023-09-27" @default.
- W2771677500 title "Structural Assessment and Sensor Placement Strategy for Self-Aware Aerospace Vehicles" @default.
- W2771677500 doi "https://doi.org/10.12783/shm2017/14035" @default.
- W2771677500 hasPublicationYear "2017" @default.
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