Model updating for real time dynamic substructures based on UKF algorithm

查看全文 作　　者：Su [1,3,4]Tingli;Tang [2]Zhenyun;Peng [2]Lingyun;Bai [1,3,4]Yuting;Jin [1,3,4]Xuebo;Kong [1,3,4]Jianlei

机构地区：[1]School of Computer Information and Engineering,Beijing Technology and Business University,Beijing 100048,China;[2]The Key Laboratory of Urban Security and Disaster Engineering,Ministry of Education,Beijing University of Technology,Beijing 100124,China;[3]Beijing Key Laboratory of Big Data Technology for Food Safety,Beijing Technology and Business University,Beijing 100048,China;[4]China Light Industry Key Laboratory of Industrial Internet and Big Data,Beijing Technology and Business University,Beijing 100048,China

出　　处：《Earthquake Engineering and Engineering Vibration》索引2020年第19卷第2期,共9页

基　　金：National Natural Science Foundation of China under Grant Nos.61903009,51978016 and 61673002;Beijing Municipal Education Commission under Grant No.KM201810011005。 摘　　要：Combining the advantages of numerical simulation with experimental testing,real-time dynamic substructure(RTDS)testing provides a new experimental method for the investigation of engineered structures.However,not all unmodeled parts can be physically tested,as testing is often limited by the capacity of the test facility.Model updating is a good option to improve the modeling accuracy for numerical substructures in RTDS.In this study,a model updating method is introduced,which has great performance in describing this nonlinearity.In order to determine the optimal parameters in this model,an Unscented Kalman Filter(UKF)-based algorithm was applied to extract the knowledge contained in the sensors data.All the parameters that need to be identified are listed as the extended state variables,and the identification was achieved via the step-by-step state prediction and state update process.Effectiveness of the proposed method was verified through a group of experimental data,and results showed good agreement.Furthermore,the proposed method was compared with the Extended Kalman Filter(EKF)-based method,and better accuracy was easily found.The proposed parameter identification method has great applicability for structural objects with nonlinear behaviors and could be extended to research in other engineering fields. 关键词：dynamic SUBSTRUCTURE complex NONLINEAR model NONLINEAR estimation adaptive updating CIVIL INFRASTRUCTURES

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Model updating for real time dynamic substructures based on UKF algorithm

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