Mixed-Effect Model of the Fluid Viscosity for Virtual Sensing of the Flow-Front Dynamics

Rishi Relan, Michael Nauheimer, Henrik Madsen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

26 Downloads (Pure)

Abstract

For online control and fault monitoring of the epoxy infusion in a vacuum assisted resin transfer moulding (VARTM) process, good knowledge of the current state of the flow-front is essential. Due to heterogeneous material properties and the environmental conditions, the permeability of the medium, as well as the viscosity of the epoxy, can change significantly during the epoxy infusion process. Hence, for a fast and reasonably accurate estimation of the flow-front, a virtual sensing system capable of combining the physics of the system and the measured data is needed. In this short paper, we propose a data-driven mixed-effect model for the fluid viscosity data acquired from multiple experimental. The proposed model can be easily integrated into the stochastic differential equations (SDE) based virtual sensing system for flow-front dynamics in a VARTM process.
Original languageEnglish
Title of host publicationProceedings of 2018 IEEE Sensors
Number of pages4
PublisherIEEE
Publication date2018
Pages1-4
ISBN (Print)9781538647073
DOIs
Publication statusPublished - 2018
SeriesI E E E Sensors. Proceedings
ISSN1930-0395

Keywords

  • Viscosity
  • Virtual sensing
  • Mixed-effect model

Fingerprint Dive into the research topics of 'Mixed-Effect Model of the Fluid Viscosity for Virtual Sensing of the Flow-Front Dynamics'. Together they form a unique fingerprint.

Cite this