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中国科学院大学学报 ›› 2006, Vol. 23 ›› Issue (2): 155-158.DOI: 10.7523/j.issn.2095-6134.2006.2.007

• 论文 • 上一篇    下一篇

应用BP神经网络校正铂电阻温度传感器非线性的方法

杜福嘉; 汪达兴   

  1. 1中国科学院国家天文台南京天文光学技术研究所,南京210042;


    2 中国科学院研究生院,北京 100039

  • 收稿日期:1900-01-01 修回日期:1900-01-01 发布日期:2006-03-15

Nonlinear Rectification Method of Platinum Resistance by BP Neural Network

DU Fu-Jia, WANG Da-Xing   

  1. 1 Nanjing Institute of Astronomical Optics & Technology, National Astronomical Observatories, Chinese Academy of Sciences, Nanjing 210042 China;
    2 Graduate School of the Chinese Academy of Sciences, Beijing 100039,China
  • Received:1900-01-01 Revised:1900-01-01 Published:2006-03-15

摘要: 本文应用BP神经网络算法对铂电阻温度传感器进行非线性校正,给出了BP神经网络的结构和训练权值的方法,在训练网络时对输入量进行了归一化处理。并应用此训练的网络对一实际的温度采集系统进行校正。此方法实现简单,大大方便了铂电阻温度传感器在温度测量中的应用。

关键词: 铂电阻, 非线性校正, BP神经网络

Abstract: This article uses BP neural network to calibrate nonlinear characteristic of platinum resistance, gives the structure of BP neural network and the method to train weight. The input are normalized when train the network. Finally, this neural network calibrates a fact system. This method can be achieved very easily. Using platinum becomes very convenience in measurement through this method

Key words: Platinum resistance, Nonlinear calibration, BP neural network

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