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Intelligent Control of Cabin Environment Using Computational Fluid Dynamics for Intelligent Manufacturing

Xi Wang*, Guangping Zeng

School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, 100083, China

* Corresponding Author: Xi Wang. Email: email

(This article belongs to the Special Issue: EFD and Heat Transfer III)

Fluid Dynamics & Materials Processing 2022, 18(3), 563-576. https://doi.org/10.32604/fdmp.2022.017884

Abstract

An efficient and versatile intelligent algorithm is developed for the control of the cabin environment of wind power generators. The method can be used to monitor and solve wind power generation problems at the same time. It also provides several advantages with respect to other traditional methods which imply significant workload and maintenance personnel. The functional requirements of the intelligent control system are analyzed, and a control algorithm for the stepping motor is selected and evaluated. Through the comparative analysis of the active power and internal temperature curve for three kinds of output power of the prototype, it is proved that the environmental intelligent control system greatly improves the operation efficiency, solves typical problems in the ventilator room environment, and provides a solid theoretical basis for further research in this field.

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APA Style
Wang, X., Zeng, G. (2022). Intelligent control of cabin environment using computational fluid dynamics for intelligent manufacturing. Fluid Dynamics & Materials Processing, 18(3), 563-576. https://doi.org/10.32604/fdmp.2022.017884
Vancouver Style
Wang X, Zeng G. Intelligent control of cabin environment using computational fluid dynamics for intelligent manufacturing. Fluid Dyn Mater Proc. 2022;18(3):563-576 https://doi.org/10.32604/fdmp.2022.017884
IEEE Style
X. Wang and G. Zeng, "Intelligent Control of Cabin Environment Using Computational Fluid Dynamics for Intelligent Manufacturing," Fluid Dyn. Mater. Proc., vol. 18, no. 3, pp. 563-576. 2022. https://doi.org/10.32604/fdmp.2022.017884



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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