<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The current wind silk-feeding system in cigarette factories has defects such as randomness, uncertainty, and frequent changes in wind volume, which are the fundamental causes of the system’s non-energy saving and unstable silk-feeding wind speed. This paper proposes to construct a new wind silk feeding system based on fuzzy RBF by utilizing the functional equivalence of fuzzy inference systems and RBF neural networks from a global perspective. Then, according to the process characteristics of the wind balance control system, the use of fuzzy networks for PID control of the core system is proposed. The practical application of the new wind power silk feeding system confirms the energy-saving effect of the improved program. Measurement results show that after the improvement of the fan frequency from 50Hz down to 38Hz, power from 35kW down to 25kW, the system runs smoothly, the wind speed is stable, and the energy saving can be up to 25%~40%. This paper not only provides a new way of thinking for the optimal design of wind power wire feeding projects but also has reference value for guiding the selection and control scheme of the project.</p>
</abstract>

The current wind silk-feeding system in cigarette factories has defects such as randomness, uncertainty, and frequent changes in wind volume, which are the fundamental causes of the system’s non-energy saving and unstable silk-feeding wind speed. This paper proposes to construct a new wind silk feeding system based on fuzzy RBF by utilizing the functional equivalence of fuzzy inference systems and RBF neural networks from a global perspective. Then, according to the process characteristics of the wind balance control system, the use of fuzzy networks for PID control of the core system is proposed. The practical application of the new wind power silk feeding system confirms the energy-saving effect of the improved program. Measurement results show that after the improvement of the fan frequency from 50Hz down to 38Hz, power from 35kW down to 25kW, the system runs smoothly, the wind speed is stable, and the energy saving can be up to 25%~40%. This paper not only provides a new way of thinking for the optimal design of wind power wire feeding projects but also has reference value for guiding the selection and control scheme of the project.

Research and development of low-energy and high-efficiency wind-fed tobacco technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

The current wind silk-feeding system in cigarette factories has defects such as randomness, uncertainty, and frequent changes in wind volume, which are the...

Research and development of low-energy and high-efficiency wind-fed tobacco technology

Publié en ligne: 05 juil. 2024

Pages: -

Reçu: 28 févr. 2024

Accepté: 21 mai 2024

DOI: https://doi.org/10.2478/amns-2024-1637

Mots clés
Wind-powered wire feeding system, Fuzzy inference, RBF neural network, PID control, Energy saving effect

© 2024 Yueping Guo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research and development of low-energy and high-efficiency wind-fed tobacco technology

Publié en ligne: 05 juil. 2024

Pages: -

Reçu: 28 févr. 2024

Accepté: 21 mai 2024

DOI: https://doi.org/10.2478/amns-2024-1637

Mots clésWind-powered wire feeding system, Fuzzy inference, RBF neural network, PID control, Energy saving effect

© 2024 Yueping Guo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Wind-powered wire feeding system, Fuzzy inference, RBF neural network, PID control, Energy saving effect