Speakers
Mariana Handman Padilha
(Universidade Federal do Pampa (UNIPAMPA), Brasil)
Maurício da S. R. Mombach
(Universidade Federal do Pampa (UNIPAMPA), Brasil)
Leandro Ferreira Friedrich
(Universidade Federal do Pampa (UNIPAMPA), Brasil)
Vicente Bergamini Puglia
(Universidade Federal do Pampa (UNIPAMPA), Brasil)
Mikael da Cruz
(Universidade Federal do Pampa (UNIPAMPA), Brasil)
Alessandro G. Girardi
(Universidade Federal do Pampa (UNIPAMPA), Brasil)
Ignacio Iturrioz
(Federal University of Rio Grande do Sul (UFRGS), Brasil)
Description
This study presents an acoustic emission (AE) monitoring strategy based on MEMS (Micro-Electro-Mechanical Systems) sensors applied to 3D-printed structures. AE data were analyzed using the b-value method to track damage development and Natural Time (NT) analysis to identify the onset of critical conditions. A comparison with a commercial piezoelectric sensor revealed similar performance, with both sensors detecting a reduction in the b-value preceding failure. MEMS sensors demonstrated an enhanced capacity to capture high-frequency signals. These results underline the potential of MEMS sensors as cost-effective tools for structural health monitoring in additive manufacturing contexts.