Dynamic Model-based Digital Twin for Crack Detection of Aeroengine Disk

Yang, Yuangui; Ma, Meng; Zhou, Zheng; Sun, Chuang; Yan, Ruqiang

doi:10.1109/icsmd53520.2021.9670836

Cited by 4 publications

(1 citation statement)

References 16 publications

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“…Ward et al [ 19 ] proposed a model-based machining DT system for a case study of a large-scale CNC machine tool using a MATLAB/Simulink platform. Yang et al [ 20 ] developed a model-based DT of an aero-engine disk for online detection of disk unbalance and crack failure using an ANSYS simulation platform. Woitsch et al [ 21 ] proposed a meta-model of a model-based DT environment to bridge the between the manufacturing and the use of products and services based on an ADOxx meta-modeling platform.…”

Section: Dt Architecture Categorizationsmentioning

confidence: 99%

Overview of Digital Twin Platforms for EV Applications

Ibrahim

Rjabtšikov

Zequera

2023

Sensors

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Digital twin (DT) technology has been used in a wide range of applications, including electric vehicles. The DT platform provides a virtual representation or advanced simulation of a physical object in real-time. The implementation of DT on various aspects of EVs has recently transpired in different research studies. Generally, DT can emulate the actual vehicle on the road to predict/optimize its performance and improve vehicle safety. Additionally, DT can be used for the optimization of manufacturing processes, real-time condition monitoring (at all levels and in all powertrain components), energy management optimization, repurposing of the components, and even recycling processes. This paper presents an overview of different DT platforms that can be used in EV applications. A deductive comparison between model-based and data-driven DT was performed. EV main systems have been discussed regarding the usable DT platform. DT platforms used in the EV industry were addressed. Finally, the review showed the superiority of data-driven DTs over model-based DTs due to their ability to handle systems with high complexity.

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Section: Dt Architecture Categorizationsmentioning

confidence: 99%