Abstrakti
A digital twin test bench was created to demonstrate the digital twin concept for control and prediction of the dynamic behavior of a paper machine roll. The paper presents a complete proof of concept digital twin system with wireless sensoring with flexible measurement patterns, data transfer, storage and visualization in an interactive 3D view. A virtual sensor based on a recurrent neural network was created to predict the middle cross section center point movement of a large flexible rotor based on acceleration and force input measured from bearing housings at the ends of the rotor. The results show that a neural network algorithm is feasible for predicting the dynamic behaviour of the rotor system. Future research at Aalto University aims to apply sensor fusion data as input to non-physics based models with the goal to predict key performance indicators of complex mechanical systems.
Alkuperäiskieli | Englanti |
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Otsikko | Proceedings of the 30th International DAAAM Symposium ''Intelligent Manufacturing & Automation'' |
Kustantaja | DAAAM International |
Sivut | 1115-1121 |
ISBN (painettu) | 978-3-902734-22-8 |
DOI - pysyväislinkit | |
Tila | Julkaistu - 2019 |
OKM-julkaisutyyppi | A4 Artikkeli konferenssijulkaisuussa |
Tapahtuma | International DAAAM Symposium on Intelligent Manufacturing and Automation - Zadar, Kroatia Kesto: 23 lokak. 2019 → 26 lokak. 2019 Konferenssinumero: 30 |
Julkaisusarja
Nimi | Annals of DAAAM and Proceedings |
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Kustantaja | DAAAM International |
Numero | 1 |
Vuosikerta | 30 |
ISSN (painettu) | 1726-9679 |
Conference
Conference | International DAAAM Symposium on Intelligent Manufacturing and Automation |
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Maa/Alue | Kroatia |
Kaupunki | Zadar |
Ajanjakso | 23/10/2019 → 26/10/2019 |