基于神经网络的智能变频抽油烟机的研究与实现

文中旨在研究一种新式抽油烟机的智能变频技术,通过对烹饪环境的综合分析,确定所需排风量,进而以一个最适宜的转速进行排烟,达到节能降耗的目的。采用神经网络控制器,在无被控对象数学模型情况下,实现转速与油烟、蒸汽两输入变量的非线性映射。仿真和实物测试结果显示:采用神经网络控制能较好实现厨房环境的实时调控,能够快速响应,具有良好的动态和稳态性能。

Research and implementation of the intelligent exhaust fan based on neural network

Frequency conversion technology on a new generation of intelligent range hood is studied.According to the comprehensive analysis of the kitchen environment,we determine the exhaust air output needed,so the range hood can discharge smoke in a most suitable speed,and achieve the purpose of saving energy and reducing consumption.The neural network controller works out the two input variables nonlinear mapping to the speed with no object mathematical model.The simulation and actual testing results show that the neural network control realize the real-time regulation in the kitchen environment primely,enhances the system sensitivity,and improve the dynamic and the stationary behavior of the system.