Supervised and Unsupervised AI-Driven Structural Health Monitoring Framework for Additively Manufactured Metal Components
Structural health monitoring (SHM) of additively manufactured (AM) small and complex components is investigated using a sensor-based signal processing and machine-learning framework. Guided-wave responses acquired from piezoelectric transducers are analyzed to evaluate the performance of sweep-sine...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI AG
2026-06-01
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| coleção: | Sensors |
| Assuntos: | |
| Acesso em linha: | https://www.mdpi.com/1424-8220/26/11/3547 |
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