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...

Cijeli opis

Bibliografski detalji

Glavni autori:	Romaine Byfield, Ahmed Shabaka, Ibrahim Tansel
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2026-06-01
Serija:	Sensors
Teme:	structural health monitoring piezoelectric transducers signal processing time–frequency analysis machine learning deep learning
Online pristup:	https://www.mdpi.com/1424-8220/26/11/3547
Oznake:	Dodaj oznaku Bez oznaka, Budi prvi tko označuje ovaj zapis!