On-line estimation of dynamic displacements by multi-rate data fusion based on kalman filter with unknown input

摘要：

　　The effective estimation of structural dynamic displacement is still a challenging task.To solve the difficulties and drawbacks of direct dynamic displacement monitoring,some improved techniques based on Kalman filter(KF)by fusing biased high-sampling rate acceleration and low-sampling rate displacement measurements have been developed in recent years.However,these techniques can only take the constant acceleration bias into account.In this paper,according to the Kalman filter with unknown input(KF-UI)proposed by the authors,dynamic displacement is on-line estimated based on multi-rate data fusion of biased high-sampling rate acceleration and low-sampling rate displacement measurements.The acceleration bias is treated as unknown input information to overcome the limitations of the previous techniques.The highlight of the proposed algorithm is that the bias of the measured acceleration is not only a constant.Furthermore,linear and polynomial bias are applied in this paper,which extends the acceleration bias to a general case.Some numerical examples considering linear or polynomial acceleration bias are performed to demonstrate the effectiveness of the proposed approach for on-line estimation of structural dynamic displacement.

关键词： dynamic displacement on-line estimation KF-UI multi-rate sampling data fusion acceleration bias

作者: Hao Qiu Zhichao Wang Ning Yang Ying Lei

作者单位: Department of Civil Engineering,Xiamen University,Xiamen,China Department of Instrumental and Electrical Engineering,Xiamen University,Xiamen,China

会议类型: 国际会议

会议名称: The 7th World Conference on Structural Control and Monitoring(7WCSCM)(第七届结构控制与监测世界大会)

会议地点: 青岛

会议语种:英文

页码: 2786-2794

在线出版日期: 2018-07-22（万方平台首次上网日期，不代表论文的发表时间）