MEMS Gyroscope Null Drift and Compensation Based on Neural Network

被引：17

作者：

Shiau, Jaw-Kuen ^{[1
]}

Ma, Der-Ming ^{[1
]}

Huang, Chen-Xuan ^{[1
]}

Chang, Ming-Yu ^{[1
]}

机构：

[1] Tamkang Univ, Dept Aerosp Engn, Tamsui 25137, Taiwan

来源：

ADVANCES IN CIVIL ENGINEERING, PTS 1-6 | 2011年 / 255-260卷

关键词：

gyroscope null drift; temperature compensation; neural network;

D O I：

10.4028/www.scientific.net/AMR.255-260.2077

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

This study investigates the effects of temperature on micro-electro mechanical system (MEMS) gyroscope null drift and methods and efficiency of temperature compensation. First, this study uses in-house-designed inertial measurement units (IMUs) to perform temperature effect testing. The inertial measurement unit is placed into the temperature control chamber. Then, the temperature is gradually increased from 25 degrees C to 80 degrees C at approximately 0.8 degrees per minute. After that, the temperature is decreased to -40 degrees C and then returning to 25 degrees C. During these temperature variations, the temperature and static gyroscope output observes the gyroscope null drift phenomenon. The results clearly demonstrate the effects of temperature on gyroscope null voltage. A temperature calibration mechanism is established by using a neural network model. With the temperature calibration, the attitude computation problem due to gyro drifts can be improved significantly.

引用

页码：2077 / 2081

页数：5

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