Multi-sensor data registration for bridge health monitoring

Abstract

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-time coordinates system. To improve accuracy of the measurements, Kalman filter is applied to reduce the system error after the data registration. The simulation results show that the methods significantly improve the credibility and accuracy of data in multi-sensor networks for bridge health monitoring.