Research on adjust speed control system of partial fan
Combining with ventilation requirements and safety regulation in coalmine, control strategy which aims at both safety and energy saving is established at length. Moreover, conventional double fuzzy control model is found to carry out two work mode, normal ventilation and gas discharging. Since four input signals affect output in different degree, three layers BP neural network is employed to compute weight. Based on conventional fuzzy model, self learning fuzzy model for partial fan is build to tackle with normal ventilation and gas discharging problem. Direct torque control style is applied to perform speed adjusting of partial fan. In order to testify the control strategy, an experiment platform including DSP and IPM is founded. The experiment results show that the control strategy is effective to fulfill the function of ventilation and gas discharge in heading laneway.
gas discharging heading laneway self learning fuzzy control model DSP
Shufang Wang Ruiyang Chen Xin Fang Jianbo Wang
School of Mechanical Electronic in Beijing Union University, Beijing 100020 P.R.China Luxin investment consultation limited company in Lu An Shan xi province 046204 P.R.China
国际会议
2007 IEEE International Conference on Automation and Lofistics
山东济南
英文
2007-08-18（万方平台首次上网日期，不代表论文的发表时间）