| 差压传感器非线性特性研究 |
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| 引用本文： | 王菖,付敬奇,陈关君.差压传感器非线性特性研究[J].传感器与微系统,2007,26(10):48-50. |
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| 作者姓名： | 王菖 付敬奇 陈关君 |
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| 作者单位： | 1. 上海大学,机电工程与自动化学院,上海,200072
2. 中国电子科技集团公司,第四十九研究所,黑龙江,哈尔滨,150001 |
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| 基金项目： | 上海市科委科技开发专项计划 |
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| 摘 要： | 介绍了一种智能差压传感器,针对影响传感器准确度的输出—输入非线性问题进行了研究。采用了BP神经网络来建立差压传感器的输出—输入模型,网络模型采用了三层结构,输出—输入层各自采用了一个神经元,将神经网络的均方误差目标值设定为10-6,并在MATLAB中进行了仿真,经训练得到的输出—输入模型的非线性误差可以达到±0.032%。通过与多项式拟合方法和最小二乘直线拟合方法所得结果进行比较,结果表明:采用BP神经网络方法对提高智能差压传感器的测量准确度具有参考价值。
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| 关 键 词： | BP神经网络 差压传感器 非线性特性 |
| 文章编号： | 1000-9787（2007）10-0048-03 |
| 修稿时间： | 2007-03-10 |
Research on non-linearity characteristics of differential pressure transducer |
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| WANG Chang,FU Jing-qi,CHEN Guan-jun.Research on non-linearity characteristics of differential pressure transducer[J].Transducer and Microsystem Technology,2007,26(10):48-50. |
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| Authors: | WANG Chang FU Jing-qi CHEN Guan-jun |
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| Affiliation: | 1. School of Machinery Electric and Automation, Shanghai University, Shanghai 200072, China; 2. The 49th Research Institute of China Electronics Technology Group Corporation, Harbin 150001, China |
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| Abstract: | A type of smart DPT is presented.The input-output non-linearity problem that affects the measurement accuracy of transducer is researched.And BP neural network is used to build the input-output model,and the BP network contains 3 layers.Either input layer or output layer contains only one neuron.The neural network is simulated in MATLAB.With mean square error setting to 10(-6),the non-linearity error of the trained input-output model can achieve ±0.032 %.The polynomial curve fitting and the least-squares line fitting are also adopted.The comparison of the results of the three methods shows that BP network model can improve the performance of DPT. |
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| Keywords: | BP neural network differential pressure transducer(DPT) non-linearity characteristics |
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