Experimental Study on Damage Detection Using an Improved Extended Kalman Filter

摘要：

　　As a popular tool for optimal estimation of system state from noisy measurement, extended Kalman filter (EKF) has been successfully used in a variety of areas over the past few decades.This paper focuses on u sing EKF for real-time system identification and damage detection of civil structures.Following a discussion of problems associated with classical EKF in time-varying systems, an improved EKF approach is proposed in this paper by using moving-window technique and variable forgetting factor.Compared with classical EKF,the improved EKF is more robust and adaptive in structural damage detection.Its salient features are illustra ted through experimental study of a three-story steel shear building model.The results of this paper demon strate that the improved EKF is a robust and effective tool for system identification and damage detection of civil structures.

作者: Zhilu Lai Songye Zhu Ying Lei Youlin Xu Xiaohua Zhang

作者单位: Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, K Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, K Department of Civil Engineering, Xiamen University, Xiamen, China

会议类型: 国际会议

会议名称: The 5th International Symposium on Innovation & Sustainability of Structures in Civil Engineering (ISISS2013)(第五届创新和可持续发展土木工程结构国际学术研讨会)

会议地点: 哈尔滨

会议语种:英文

页码: 674-680

在线出版日期: 2013-07-06（万方平台首次上网日期，不代表论文的发表时间）