测试技术学报2011，Vol.25Issue(3)：278-282,5.DOI:10.3969/j.issn.1671-7449.2011.03.019
基于BP神经网络的磁通门传感器温度误差补偿
Temperature Compensation of Fluxgate Magnetometer Based on BP Neural Network
庞鸿锋 1罗诗途 1陈棣湘 1潘孟春 1张琦1
作者信息
- 1. 国防科学技术大学机电工程与自动化学院,湖南长沙410073
- 折叠
摘要
Abstract
Accuracy of fluxgate magnetometers is badly influenced by temperature change. Temperature characteristic of magnetometer output was researched in different magnetic circumstances by nonmagnetic temperature experiment box, and then, BP Neural Network was used to compensate error caused by temperature. Experimental process and data processing method were introduced in detail. Firstly, sample data were obtained at different temperatures. Then, BP Neural Network was used in temperature error modeling and compensation network training, and temperature error was compensated in different magnetic circumstances.Finally, testing data temperature error was compensated by the trained network. It demonstrates that temperature error is reduced from 195.6 nT, 203.2 nT, 213.6 nT to 17.18 nT, 18.89 nT, 18.04 nT, respectively. Obviously, temperature error is suppressed greatly, which proves good performance of BP neural network in fluxgate magnetometers calibration.关键词
磁通门传感器/BP神经网络/非线性逼近/温度误差/补偿Key words
fluxgate magnetometers/ BP neural Network/ nonlinear approach/ temperature error/ compensation分类
机械制造引用本文复制引用
庞鸿锋,罗诗途,陈棣湘,潘孟春,张琦..基于BP神经网络的磁通门传感器温度误差补偿[J].测试技术学报,2011,25(3):278-282,5.
