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Digital twin of a pipe conveying fluid: flow rate anomaly detection and quantification via multi-fidelity kalman filters and event based cameras signals

Vincent Laperle, Esmaeil Ghorbani, Quentin Dollon et Frederick Gosselin

Ensemble de données (2025)

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Abstract

Numerical results of a digital twin (DT) framework for a pipe conveying fluid recorded using two event-based cameras (EVB). The DT framework consists of an unscented Kalman filter (UKF) for parameter identification and a linear Kalman filter (LKF) coupled with dynamic mode decomposition (DMD) for real-time monitoring and anomaly detection.

The test case concerns a 75-second recording with a time interval of 0.025 s for a change in flow velocity in the pipe carrying the fluid occurring at t = 18.4 s. The flowrate is the unknown parameter and is initialized as 5.84 m/s and is then reduced to 5.21 m/s. Details of the implementation are available in the associated article.

Département: Département de génie mécanique
URL de PolyPublie: https://publications.polymtl.ca/70169/
Source: Zenodo
Maison d'édition: CERN
DOI: 10.5281/zenodo.17282131
Autres DOI associés à ce document: 10.5281/zenodo.17282132
URL officielle: https://doi.org/10.5281/zenodo.17282131
Date du dépôt: 04 déc. 2025 14:37
Dernière modification: 04 déc. 2025 14:37
Citer en APA 7: Laperle, V., Ghorbani, E., Dollon, Q., & Gosselin, F. (2025). Digital twin of a pipe conveying fluid: flow rate anomaly detection and quantification via multi-fidelity kalman filters and event based cameras signals [Ensemble de données]. Zenodo. https://doi.org/10.5281/zenodo.17282131

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