| 基于人工神经网络技术的光电信息检测研究 |
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| 引用本文： | 李晶晶.基于人工神经网络技术的光电信息检测研究[J].科学技术与工程,2011,11(5):1084-1087. |
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| 作者姓名： | 李晶晶 |
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| 作者单位： | 东北石油大学电子科学学院,大庆,163318 |
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| 摘 要： | 本文分析了引起光电检测系统非线性误差的因素。在基于光电二极管的光照度检测实验中,应用RBF人工神经网络对光信号和电信号进行非线性误差补偿,实现了在不同环境温度下,光信号与电信号的线性转换,有效地提高光照度检测的检测精度。
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| 关 键 词： | 光照度 RBF人工神经网络 光电二极管 |
| 收稿时间： | 2010/11/17 0:00:00 |
| 修稿时间： | 2010/11/26 0:00:00 |
The Research Of Optical Information Inspection Based On Artificial Neural Network |
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| lijingjing.The Research Of Optical Information Inspection Based On Artificial Neural Network[J].Science Technology and Engineering,2011,11(5):1084-1087. |
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| Authors: | lijingjing |
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| Institution: | WANG Li-gang,LI Jing-jing,JIAN Tian-cheng(Colledge of Electronics,Northeast Petroleum University,Daqing 163318 P.R.China) |
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| Abstract: | The elements are analyzed which cause non-linear error of photoelectric detection system.On the experiment of illuminance measurement based on photodiode,RBF artificial neural network is applied to achieve non-linear compensation between light signal and electronic signal.This method can realize the linear transformation between them in the different environment temperature,and improve detection accuracy of illuminance measurement effectively. |
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| Keywords: | illuminance RBF artificial neural network photodiode |
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