Automatic Generation of a Simulation-based Digital Twin of an Industrial Process Plant

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Tutkijat

Organisaatiot

  • Luleå University of Technology

Kuvaus

A Digital Twin (DT) of a production plant is a digital replica of the plant’s physical assets which contains the structure and the dynamics of how the devices and process operate. Simulation-based DTs (SBDTs) are those based on online first principle simulation models. In these systems, model parameter estimation techniques keep an online plant simulator in the same state as the targeted device or process. As a result, non-measured information of the current state of the plant can be obtained from the model. SBDTs can be used for a number of important applications and they have various advantages compared to DTs based on data-driven models. However, wider industrial adoption of SBDTs is hindered by laborious development of their underlying first principle simulation model as well as by a lack of integrated lifecycle-wide implementation methods and simulation architectures. This paper focuses on applying previously presented methods for reducing implementation effort of SBDTs. Firstly, laborious simulation model development is tackled by applying an automatic model generation method. Secondly, an integrated implementation methodology of a lifecycle-wide online simulation architecture is followed for developing the SBDT. The results show a higher level of fidelity compares to previous publications. A SBDT of a laboratory-scale process is implemented to demonstrate the proposed method.

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoProceedings of the 44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018
TilaJulkaistu - 2018
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaAnnual Conference of the IEEE Industrial Electronics Society - Washington, Yhdysvallat
Kesto: 21 lokakuuta 201823 lokakuuta 2018
Konferenssinumero: 44

Julkaisusarja

NimiProceedings of the Annual Conference of the IEEE Industrial Electronics Society
KustantajaIEEE
ISSN (painettu)1553-572X

Conference

ConferenceAnnual Conference of the IEEE Industrial Electronics Society
LyhennettäIECON
MaaYhdysvallat
KaupunkiWashington
Ajanjakso21/10/201823/10/2018

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