桥梁健康监测中多传感器的时空数据配准分析

 针对桥梁健康监测中多传感器数据的可信性及准确性问题,提出了一种二维数据处理模型.首先利用最小二乘法对异步测量数据进行时间配准,再通过几何坐标转换算法进行空间配准,将测量数据置于同一个时间和空间的坐标系中,使得数据具有可信性;并在时空数据配准处理后利用卡尔曼滤波的方法减小系统误差,这样数据具有了准确性.仿真结果表明:该模型有效提高了桥梁健康监测中传感器网络所采集数据的可信性与准确性.

Multi-sensor data alignment for bridge health monitoring

Aimed at the problem of credibility and accuracy exiting in multi-sensor data for bridge health monitoring,this paper presents a model based on two-dimensional data processing.To make reliability of the measurements,first asynchronous data are equalized by the least square algorithm,and through the geometric coordinate transformation algorithm,measurements will be placed in the same space and time coordinate system.To improve accuracy of the measurements,Kalman filter is applied to reduces the system error after the data alignment.The simulation results show that the methods significantly increase the credibility and accuracy of data in multi-sensor networks for bridge health monitoring.