煤矿井下微机电系统陀螺随机误差辨识

基金项目:

“十三五”国家科技重大专项资助项目（2016ZX05045002-005）。

详细信息

Random error identification for MEMS gyro in coal mine underground

摘要: 针对常用随机误差辨识方法不能揭示潜在的误差源、很难分离出具体随机误差、数据采集时间过长等问题，利用Allan方差分析法对煤矿井下微机电系统（MEMS）陀螺随机误差进行辨识。介绍了Allan方差分析法原理，利用Allan方差分析法对MEMS陀螺实测数据进行处理，给出了Allan标准差曲线，通过最小二乘拟合得到MEMS陀螺的主要随机误差系数。实验结果验证了Allan方差分析法用于MEMS陀螺随机误差辨识的有效性。
- 钻孔测斜 /
- 微机电系统陀螺 /
- 随机误差 /
- 误差辨识 /
- Allan方差
Abstract: Aiming at problems of unrevealing potential error source, hardly separating specific random error and long data collection time of common random error identification methods, Allan variance analysis method was used to identify random error of MEMS gyro in coal mine underground. Principle of Allan variance analysis method was introduced. Allan variance analysis method was used to process measured data of MEMS gyro, Allan standard deviation curves were given, and main random error coefficients of MEMS gyro were obtained by least square fitting. The experiment results verify validity of the Allan variance analysis method for random error identification of MEMS gyro.
- borehole clinometer /
- MEMS gyro /
- random error /
- error identification /
- Allan variance