| 基于遗传算法的RBF神经网络在涡流传感器非线性补偿中应用 |
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| 引用本文： | 俞阿龙,.基于遗传算法的RBF神经网络在涡流传感器非线性补偿中应用[J].电子器件,2008,31(3):1039-1041. |
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| 作者姓名： | 俞阿龙 |
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| 作者单位： | 淮阴师范学院电子与电气工程系,江苏,淮安,223001 |
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| 基金项目： | 江苏省高校自然科学基金
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淮阴师范学院博士基金 |
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| 摘 要： | 为了解决涡流传感器的非线性问题,应用遗传算法(GA)训练径向基函数(RBF)神经网络(NN)实现其非线性补偿.介绍非线性补偿的原理和网络训练方法.从实测数据出发,建立了涡流传感器的非线性补偿模型.该方法能同时优化网络结构和参数,具有全局寻优能力,补偿精度高、鲁棒性好、网络训练速度快、能实现在线软补偿.实验结果表明,所采用的涡流传感器非线性补偿方法是有效的和可行的.补偿后,最大非线性误差在0.5%范围内,具有良好的线性.
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| 关 键 词： | 涡流传感器 非线性补偿 径向基函数神经网络 遗传算法 基于遗传算法 神经网络 涡流传感器 线性补偿 应用 RBF Neural Network Genetic Algorithm Based Method Compensation Current Sensor 范围 线性误差 补偿方法 结果 实验 在线 训练速度 鲁棒性 补偿精度 |
| 文章编号： | 1005-9490(2008)03-1039-03 |
| 修稿时间： | 2007年5月31日 |
Eddy Current Sensor Non-Linearity Compensation Method Based on Genetic Algorithm and RBF Neural Network |
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| YU A-long.Eddy Current Sensor Non-Linearity Compensation Method Based on Genetic Algorithm and RBF Neural Network[J].Journal of Electron Devices,2008,31(3):1039-1041. |
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| Authors: | YU A-long |
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| Affiliation: | YU A-long(Department of Electronic , Electrical Engineering,Huaiyin Teachers College,Huaian Jiangsu 223001,China) |
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| Abstract: | A method used to the eddy current sensor non-linearity compensation is applied based on RBF neural network that is trained by genetic algorithms to settle its non-linear problem. The principle and algorithms of neural network are introduced. In this method, the configuration and parameters of non-linearity compensation model are optimized by genetic algorithm.The non-linear compensation model is set up by RBF neural network according to measurement data.The proposed non-linearity compensation method has hig... |
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| Keywords: | eddy current sensor non-linearity compensation RBF neural network genetic algorithm |
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