摘要
以一种橡胶阀双腔体并联泵为例,在输入110V正弦交流信号时,测得该压电薄膜泵的输出流量及出口压力的值。在实验数据的基础上,应用BP神经网络建立了压电泵输入输出系统的映射关系,并利用Matlab/Simulink提供的模块搭建了压电泵的模型。结果表明,通过BP神经网络得到的输出特性值具有较高的精度,能客观地反映压电泵输出特性随输入频率的变化关系。
Taking a rubber valve dual-chamber parallel pump as an example, the output flow and pressure of this piezoelectric film pump were measured after imputing 110 V AC sine signal to it. Based on the experimental data, mapping relations of the piezoelectric pump input-output system were established by using the model of BP neural networks and the model of this piezoelectric pump was established using modules provided by Matlab/Simulink. Research shows that the values of output characteristics are very accurate by applying BP neural networks, which can objectively show the relations of output characteristics and input frequencies of a piezoelectric pump.
出处
《机床与液压》
北大核心
2010年第7期95-98,共4页
Machine Tool & Hydraulics
基金
国家自然科学基金项目(50575093)
教育部高等学校科技创新工程重大项目培育资金资助项目(708028)
关键词
BP神经网络
压电泵
辨识
模型
BP neural networks
Piezoelectric pump
Identification
Model
