Magnetic bearing: structure, model, and control strategy

Huang, Zhihang; Li, Changhe; Zhou, Zongming; Liu, Bo; Zhang, Yanbin; Yang, Min; Gao, Teng; Liu, Mingzheng; Zhang, Naiqing; Sharma, Shubham; Dambatta, Yusuf Suleiman; Li, Yongsheng

doi:10.1007/s00170-023-12389-8

Cited by 5 publications

(2 citation statements)

References 209 publications

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“…The results indicated that the optimum temperature and pH were 30 °C and 7.5, respectively. Compared to the reported studies, 48,89 the optimum pH optima was lower than that of the controlled bilirubin based on the indirect electrochemical response. On the other hand, the results showed that the obtained relationship between the response of the biosensor and bilirubin concentration (0.01-250 mm) was linear, and the response remained constant aer 250 mm.…”

Section: Biosensor Optimizationcontrasting

confidence: 62%

A graphene oxide/polyaniline nanocomposite biosensor: synthesis, characterization, and electrochemical detection of bilirubin

Ahmed,

Hsu,

Mahmoud

et al. 2023

RSC Adv.

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Section: Biosensor Optimizationcontrasting

confidence: 62%

A graphene oxide/polyaniline nanocomposite biosensor: synthesis, characterization, and electrochemical detection of bilirubin

Ahmed,

Hsu,

Mahmoud

et al. 2023

RSC Adv.

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“…The DT model serves as the core and foundation of the DT system. A multitude of studies are model-driven and complemented by the development of virtual systems [84][85][86][87][88]. Research on DT-driven modeling of mechanical process systems can be summarized as the resolution of the underlying problem, the requirements of the modeling methodology, and the evaluation of the model [89].…”

Section: Model Constructionmentioning

confidence: 99%

Digital Twins Enabling Intelligent Manufacturing: From Methodology to Application

Hu,

Li,

et al. 2024

Intelligent and Sustainable Manufacturing

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Digital twin technology develops virtual models of objects digitally, simulating their real-world behavior based on data. It aims to reduce product development cycles and costs through feedback between the virtual and real worlds, data fusion analysis, and iterative decision-making optimization. Traditional manufacturing processes often face challenges such as poor real-time monitoring and interaction during machining, difficulties in diagnosing equipment failures, and significant errors in machining. Digital twin technology offers a powerful solution to these issues. Initially, a comprehensive review of the research literature was conducted to assess the current research scope and trends. This was followed by an explanation of the basic concepts of digital twins and the technical pathway for integrating digital twins into intelligent manufacturing including outlining the essential technologies for creating a system of interaction between the virtual and real worlds, enabling multimodel fusion, data sensing, algorithm-based prediction, and intelligent decision-making. Moreover, the application of digital twins in intelligent manufacturing throughout the product life cycle was detailed, covering product design, manufacturing, and service stages. Specifically, in the manufacturing phase, a model based on heat conduction theory and visualization was used to construct a time-varying error model for the motion axis, leading to experiments predicting the time-varying error in the hole spacing of a workpiece. These experiments achieved a minimum prediction error of only 0.2 μm compared to the actual error. By compensating for time-varying errors in real time, the variability in the hole spacing error decreased by 69.19%. This paper concludes by summarizing the current state of digital twins in intelligent manufacturing and projecting future trends in key technologies, application areas, and data use, providing a basis for further research.

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Enhanced manufacture technology based on emission reduction and carbon reduction in cutting and grinding

Li,

Zhang,

Said

2024

Int J Adv Manuf Technol

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Magnetic bearing: structure, model, and control strategy

Cited by 5 publications

References 209 publications

A graphene oxide/polyaniline nanocomposite biosensor: synthesis, characterization, and electrochemical detection of bilirubin

A graphene oxide/polyaniline nanocomposite biosensor: synthesis, characterization, and electrochemical detection of bilirubin

Digital Twins Enabling Intelligent Manufacturing: From Methodology to Application

Enhanced manufacture technology based on emission reduction and carbon reduction in cutting and grinding

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