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

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.