Szczegóły publikacji
Opis bibliograficzny
SYPIN: a system for data processing and interpretation for Structural Health Monitoring / Ziemowit DWORAKOWSKI // W: Advances in Technical Diagnostics II : proceedings of the 7th International Congress on Technical Diagnostics, ICTD 2022 : 14–16 September 2022, Radom, Poland / eds. Andrzej Puchalski, [et al.]. — Cham : Springer Nature Switzerland, cop. 2023. — (Applied Condition Monitoring ; ISSN 2363-698X ; vol. 21). — ISBN: 978-3-031-31718-7; e-ISBN: 978-3-031-31719-4. — S. 123–130. — Bibliogr., Abstr. — Publikacja dostępna online od: 2023-05-21
Autor
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 147064 |
|---|---|
| Data dodania do BaDAP | 2023-06-05 |
| DOI | 10.1007/978-3-031-31719-4_13 |
| Rok publikacji | 2023 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Czasopismo/seria | Applied Condition Monitoring |
Abstract
Recent years have seen a tremendous development of artificial-intelligence-based solutions. Although many areas of science and engineering were affected by this rapid growth, Structural Health Monitoring (SHM) appears to benefit from it to a relatively low extent. Despite the invention of methods that work with raw data, are general, and can be used to solve many complex challenges, most SHM approaches involve manual configuration of signal processing and decision-making routines. In order to develop universal solutions that do not require human input at every stage of processing, it is necessary to develop frameworks and methodologies that incorporate context knowledge, the ability to transfer information between systems and structures of varying levels of similarity, and the development of a robust and diverse database for decision systems training and evaluation. All of these requirements were addressed in the scope of the SYPIN project - aimed at developing an autonomous system that can replace human experts at every stage of SHM data processing.
