基于多传感器融合的TBM姿态角测量方法  

Method of multi-sensor attitude measurement system on TBM

作　　者：张春草[1] 张剑波[1] 朱国力[1] 

机构地区：[1]华中科技大学机械科学与工程学院,湖北武汉430074

出　　处：《华中科技大学学报（自然科学版）》2015年第12期48-51,81,共5页Journal of Huazhong University of Science and Technology(Natural Science Edition)

基　　金：国家重点基础研究发展计划资助项目(2013CB035405)

摘　　要：为了解决倾角仪在硬岩掘进过程中强振动环境下的失效问题,基于倾角仪输出精度高、微型机电系统(MEMS)陀螺仪抗振动强的优点,提出了多传感融合的姿态测量方法.采用Allan方差方法建立MEMS陀螺仪的随机误差模型,并用扩展卡尔曼滤波算法对陀螺仪的零漂进行有效估计和补偿,在倾角仪失效情况下采用修正过的陀螺仪数据计算掘进机的姿态角.仿真和实验表明:该算法能有效实现振动环境下姿态测量的计算,保证多传感器融合系统误差不超过0.06°.A multi-sensor attitude measurement method was proposed to fuse information from incli- nometer and micro-electromechanical systems （MEMS） gyroscope. The virtues of two sensors were combined to overcome the difficulties of vibration caused by hard rock during tunneling and inaccura- cy. Stochastic error model of MEMS gyroscope was built on the basis of Allan variance modeling. Two sensors were fused to measure angles using extend Kalman filtering algorithm, which estimated and compensated zero bias of gyroscope with the high accurate output of inclinometer. The attitude of TBM under the strong vibration was calculated by gyroscope which was compensated using multi-sen- sor fusion algorithm. Finally, using simulation and test results, it is shown that the multiple sensor information fusion algorithm is effective and improves the accuracy of attitude measurement. It en- sures that the error of multi-sensor attitude measurement system is less than 0.06°.

关 键 词：多传感器融合 姿态测量 倾角仪 微型机电系统陀螺仪 扩展卡尔曼滤波 隧道掘进机(TBM) 

分 类 号：U455.39[建筑科学—桥梁与隧道工程]