基于光纤陀螺的大坝安全监测随机漂移误差

Random Drift Error Analysis of Fiber Optic Gyro System in Dam Safety Monitoring

光纤陀螺仪是在面板堆石坝面板挠度变形监测中应用的一种新型仪器,它在预先埋设的管道中运行。随机漂移是捷联惯导系统在大坝安全监测中运用的主要误差源,为了有效减小光纤陀螺的误差,需要对光纤陀螺的随机误差建立模型。根据时间序列建模基本原理,建立自回归滑动平均模型(ARMA),在此基础上运用卡尔曼滤波算法对光纤陀螺随机漂移信号进行滤波降噪。滤波结果和Allan方差分析表明,滤波效果较好,光纤陀螺的精度得到提高,能更好地反映大坝运行的真实情况,从而为大坝运行状况的客观评价提供可靠依据。

Fiber Optic Gyro is a new instrument for deflection monitoring of rockfill dam with face slab,which is buried in conduit in advance. Thus random drift is the main error sources in the dam safety monitoring that strapdown inertial navigation system has been applied. In order to reduce the error of FOG effectively,we need to build a model for FOG＇s random error. Based on the theory of time system,this paper built the ARMA model. According to this model,Kalman filtering algorithm was used on FOG random drift signal to noise reducing filter.Filtering results and Allan variance analysis show that the filtering effect is good and the precision of FOG has been improved at the same time,which can reflect the dam of real situation and provide reliable basis for the dam operation situation objective evaluation.