| 基于RBF神经网络的热电偶信号处理新方法 |
| |
| 引用本文： | 曾建国,陈光梦,王健. 基于RBF神经网络的热电偶信号处理新方法[J]. 传感器与微系统, 2007, 26(1): 36-38 |
| |
| 作者姓名： | 曾建国 陈光梦 王健 |
| |
| 作者单位： | 复旦大学,电子工程系,上海,200433 |
| |
| 摘 要： | 针对热电偶信号处理中的非线性校正和冷端补偿等突出问题,利用径向基函数(RBF)神经网络构造双输入单输出的网络模型,并采用遗传算法对网络结构和参数进行优化训练,同时完成了热电偶测温中的非线性校正和冷端补偿。经仿真实验证明:该方法的测量误差减小至0.095%,在较大范围内提高了热电偶温度测量的精度。
|
| 关 键 词： | 热电偶 径向基函数神经网络 遗传算法 非线性校正 冷端补偿 |
| 文章编号： | 1000-9787（2007）01-0036-03 |
| 收稿时间： | 2006-06-24 |
| 修稿时间： | 2006-06-24 |
New signal processing method for thermocouple based on RBF neural network |
| |
| ZENG Jian-guo,CHEN Guang-meng,WANG Jian. New signal processing method for thermocouple based on RBF neural network[J]. Transducer and Microsystem Technology, 2007, 26(1): 36-38 |
| |
| Authors: | ZENG Jian-guo CHEN Guang-meng WANG Jian |
| |
| Affiliation: | Department of Electronic Engineering, Fudan University, Shanghai 200433, China |
| |
| Abstract: | A method is presented to compensate non-linearity and cold-side-offset for signal processing of thermocouple.A network model with two inputs and single output is constructed by radial basis function(RBF) neural network(NN),which is trained by genetic algorithm.Under the NN model,non-linearity compensation and cold-side-offset adjustment of thermocouple are realized simultaneously.The simulation experimenls show that the testing error of this method is 0.095 %,it improves the accuracy in a wider range. |
| |
| Keywords: | thermocouple radial basis function(RBF) neural network(NN) genetic algorithm non-linearity adjustment cold-side-offset |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
