摘要
基于声表面波传感器(SAW)理论基础,研究了SAW压力传感器的输入-输出特性。并对影响其性能的主要因素———温度进行了理论和实验分析,得到了SAW压力传感器的温度特性曲线。在非线性补偿方法的基础上,采用反向传播(BP)神经网络对其进行温度补偿,达到了减小误差、提高测量准确度的目的。
Based on the theory of surface acoustic wave sensor,the input/output of surface acoustic wave pressure sensor is studied.Through analysis of the theory and experiment data,its temperature characteristic curve is obtained.And the BP neural network is used for its temperature compensation based on nonlinearity compensation method.The result shows that the error is reduced and the testing precision is improved.
出处
《传感器技术》
CSCD
北大核心
2005年第2期37-38,42,共3页
Journal of Transducer Technology
关键词
声表面波
压力
补偿
神经网络
SAW(surface acoustic wave)
pressure
compensation
neural network
