Simulation of temperature compensation of pressure sensor based on PCA and improved BP neural network

被引：3
|
作者：
Li, Teng [1 ]
Yang, Shiliang [1 ]
Pan, Hongliang [1 ]
机构：
[1] Logist Coll Air Force, Dept Aviat Ammunit, Xuzhou 221000, Peoples R China
来源：
ADVANCES IN MECHATRONICS, AUTOMATION AND APPLIED INFORMATION TECHNOLOGIES, PTS 1 AND 2 | 2014年 / 846-847卷
关键词：
Temperature Compensation; PCA; Neural network; Sensor;
D O I：
10.4028/www.scientific.net/AMR.846-847.513
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Considering the effects of temperature on output of silicon pressure sensor, this paper proposed a novel method for analyzing temperature compensation of pressure sensor by using the combination of Principal Component Analysis (PCA) and improved BP neural networks. By using PCA to extract the prime information of temperature compensation, the multi-dimensional problem is simplified, the noise error data is eliminated, the neural network is improved and the fault-tolerance capability is enhanced. The results indicate that this method can restrain the effects of temperature on pressure sensors effectively and enhance their stability and accuracy.
引用
收藏
页码：513 / 516
页数：4
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