Multi-rate kalman filtering for the data fusion of displacement and acceleration in structural health monitoring system for bridge
Numerous long span cable supported bridges have been built throughout the world in recent years.Many damage detection and system identification approaches benefit from the availability of both acceleration and displacement measurements.But the acceleration and the displacement data are getting a lot of noise.And the displacement-based sensing is that the high-frequency resolution is limited,and often relatively low sampling rates are used.In this paper,the multi-rate Kalman filter is adopted for the data fusion of displacement and acceleration,which were sampled at different frequencies.And then,a smoothing step is proposed to obtain improved accuracy in the displacement estimate.Finally,the validity of the proposed method is demonstrated by a real-world bridge-River Bridge.The River Bridge total length of the bridge is 5985.66 m and the main bridge is a two-span continuous steel truss girder cable-stayed bridge with span arrangement 50m+215m+510m+215m+50m=1040 m.The span centre displacement and acceleration response measurements in structural health monitoring system of the bridge are used for data fusion.The acceleration sampling rate is 20 Hz,and the displacement measurement rate is 1 Hz.Compared to traditional multi-rate Kalman filter,we can get more accurate acceleration and displacement measurements at the same time.The power spectrum analysis proves the effectiveness of the method.Results of this study indicate that data fusion is practical to improve the GPS and acceleration measurements accuracy.
Kalman filter Smoothing Multi-rate sampling data fusion
Yan Wang Ting-Hua Yi Hong-Nan Li
School of Civil Engineering,Dalian University of Technology,Dalian 116023,China
国际会议
The 7th World Conference on Structural Control and Monitoring(7WCSCM)(第七届结构控制与监测世界大会)
青岛
英文
2327-2331
2018-07-22（万方平台首次上网日期，不代表论文的发表时间）