KIT | KIT-Bibliothek | Impressum | Datenschutz

Supporting visualization analysis in industrial process tomography by using augmented reality—A case study of an industrial microwave drying system

Zhang, Yuchong; Omrani, Adel ORCID iD icon 1; Yadav, Rahul; Fjeld, Morten
1 Institut für Hochleistungsimpuls- und Mikrowellentechnik (IHM), Karlsruher Institut für Technologie (KIT)

Abstract:

Industrial process tomography (IPT) based process control is an advisable approach in industrial heating processes for improving system efficiency and quality. When using it, appropriate dataflow pipelines and visualizations are key for domain users to implement precise data acquisition and analysis. In this article, we propose a complete data processing and visualizing workflow regarding a specific case—microwave tomography (MWT) controlled industrial microwave drying system. Furthermore, we present the up-to-date augmented reality (AR) technique to support the corresponding data visualization and on-site analysis. As a pioneering study of using AR to benefit IPT systems, the proposed AR module provides straightforward and comprehensible visualizations pertaining to the process data to the related users. Inside the dataflow of the case, a time reversal imaging algorithm, a post-imaging segmentation, and a volumetric visualization module are included. For the time reversal algorithm, we exhaustively introduce each step for MWT image reconstruction and then present the simulated results. For the post-imaging segmentation, an automatic tomographic segmentation algorithm is utilized to reveal the significant information contained in the reconstructed images. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000138925
Veröffentlicht am 13.10.2021
Originalveröffentlichung
DOI: 10.3390/s21196515
Scopus
Zitationen: 13
Web of Science
Zitationen: 9
Dimensions
Zitationen: 15
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Hochleistungsimpuls- und Mikrowellentechnik (IHM)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2021
Sprache Englisch
Identifikator ISSN: 1424-8220
KITopen-ID: 1000138925
HGF-Programm 38.03.02 (POF IV, LK 01) Power-based Fuels and Chemicals
Erschienen in Sensors
Verlag MDPI
Band 21
Heft 19
Seiten 6515
Nachgewiesen in Scopus
Dimensions
Web of Science
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page