1. 九江学院电子工程系,江西,九江,332005
2. 合肥工业大学仪器仪表学院
3. ,安徽,合肥,230009
纸质出版:2007
移动端阅览
[1]吴德会.基于LS-SVM辨识的温度传感器非线性校正研究[J].传感器与微系统,2007(09):35-37+41.
WU De-hui1. Study on non-linearity compensation of temperature sensor based on LS-SVM[J]. 2007, (9): 35-37+41.
[1]吴德会.基于LS-SVM辨识的温度传感器非线性校正研究[J].传感器与微系统,2007(09):35-37+41. DOI: 10.13873/j.1000-97872007.09.029.
WU De-hui1. Study on non-linearity compensation of temperature sensor based on LS-SVM[J]. 2007, (9): 35-37+41. DOI: 10.13873/j.1000-97872007.09.029.
针对人工神经网络等传统方法的不足
提出了一种利用最小二乘支持向量机(LS-SVM)的热电偶非线性校正方法。在该方法中
根据正反馈原理构造形式为幂级数展开模型的非线性补偿器
并利用LS-SVM线性回归算法辨识该补偿器幂级数序列模型的系数。通过该补偿器之后
热电偶可得到理想的线性特性。最后
对铂铑30—铂铑6热电偶(B型)进行非线性校正实验
实验结果表明:在0
1
820℃范围内
校正后系统的线性度小于0.035 3。因此
所提方法有效
且能应用于其他相似系统的非线性校正。
In order to overcome the shortcoming of artificial neural networks and other conventional methods
a novel method to non-linearity compensation for thermocouple sensor using least squares support vector machine(LS-SVM) is put forward.In this method
the non-linear compensator
with power series expansion-based model
is established based on the principle of positive feedback.Meanwhile
the coefficients of power series of the compensator are identified by LS-SVM linear regression algorithm.Through this compensator
the desired linear characteristics of thermocouple can be obtained.Finally
platinum-rhodium 30-platinum-rhodium 6 thermocouple(B) sensor is taken as an example to non-linearity compensation
and experimental results show that the linearity of compensated sys
tem is less than 0.035 3 in the temperature range from 0
820 ℃.So the presented method is effective and can be also used in other similar systems..
基于SVM的传感器非线性特性校正新方法 [J]. 吴德会,王晓红,朱程辉. 工业仪表与自动化装置 . 2005(04)
基于遗传神经网络的传感器系统的非线性校正 [J]. 陈俊杰,芦俊,黄惟一. 仪器仪表学报 . 2003(02)
传感器特性曲线的自适应分段最佳拟合及应用 [J]. 朱庆保. 传感器技术 . 2002(01)
模式识别[M]. 清华大学出版社 , 边肇祺等编著, 2000
Least Squares Support Vector Machine Classifiers [J] . J.A.K. Suykens,J. Vandewalle. Neural Processing Letters . 1999 (3)
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