| Zugriffsnummer | 49065 |
| Dokumenttyp | Konferenzartikel |
| Peer Review | unbekannt |
| Sprache | Englisch |
| Titel | First steps toward leveraging artificial intelligence for precise characterisation of force transducers |
| Autor(in); Institution |
Mirian, Davood; 1.2, Festkörpermechanik, PTB-Braunschweig
Kumme, Rolf; 1.2, Festkörpermechanik, PTB-Braunschweig
Tutsch, R.; TU Braunschweig, Institut für Produktionsmesstechnik, Braunschweig, GERMANY
|
| Quelle/Jahr | IMEKO 24th TC3, TC5, TC 16 and TC22 International Conference 2022:(2022), 6 S. |
| Availability | [online only] |
| DOI | |
| URL | |
| Verlag | IMEKO |
| Konferenzangaben | IMEKO 24th TC3, 14th TC5, 6th TC16 and 5th TC22 International Conference, Cavtat, Dubrovnik, 11-13, October, 2022, Croatia |
| Freie Schlagworte | dynamic force cali ; rocking motion ; measurement uncertainty ; machine learning ; deep learning ; recurrent neural networks |
| Zusammenfassung | This work is dedicated to the demonstration of a dynamic force measurement system for precise characterisation of the force transducers. The rocking motion of the system as a main dominant source of uncertainty in the acceleration is investigated. We propose a novel method based on the application of an artificial neural network for evaluation of the data as an alternative to traditional approaches to get low-uncertainty calibration measurements. In the end, two special architectures of the artificial neural network, namely Long Short-Term Memory LSTM and Gated Recurrent Network GRU are introduced, and their appropriateness for our use case is discussed. |
| Kostenfreier Zugang | Freier Zugang |
| Themenbereich der Metrologie | Masse und abgeleitete Größen |
| Forschungsprojekt | 18SIB08: ComTraForce: Comprehensive traceability for force metrology services |
| Förderinformationen (1) |
Förderername: European Commission (EC)
Förderer ID: 0000 0001 2242 8989 Förderer ID Typ: ISNI Förderprogramm: EMPIR 2018 SI Broader Scope Titel der Förderung: 18SIB08: ComTraForce: Comprehensive traceability for force metrology services Förderungsnummer: 18SIB08 |
Zitierung
Mirian, D., Kumme, R., & Tutsch, R. (2022). First steps toward leveraging artificial intelligence for precise characterisation of force transducers. IMEKO 24th TC3, 14th TC5, 6th TC16 and 5th TC22 International Conference, Cavtat, Dubrovnik, 11-13, October, 2022, Croatia. https://doi.org/10.21014/tc3-2022.075