Decentralized identification of nonlinear structure under strong ground motion using the extended Kalman filter and unscented Kalman filter

Dongwang Tao; Hui Li; Qiang Ma

doi:10.1117/12.2218964

22 April 2016 Decentralized identification of nonlinear structure under strong ground motion using the extended Kalman filter and unscented Kalman filter

Dongwang Tao, Hui Li, Qiang Ma

Author Affiliations +

Proceedings Volume 9804, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, and Civil Infrastructure 2016; 980420 (2016) https://doi.org/10.1117/12.2218964
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2016, Las Vegas, Nevada, United States

Abstract

Complete structure identification of complicate nonlinear system using extend Kalman filter (EKF) or unscented Kalman filter (UKF) may have the problems of divergence, huge computation and low estimation precision due to the large dimension of the extended state space for the system. In this article, a decentralized identification method of hysteretic system based on the joint EKF and UKF is proposed. The complete structure is divided into linear substructures and nonlinear substructures. The substructures are identified from the top to the bottom. For the linear substructure, EKF is used to identify the extended space including the displacements, velocities, stiffness and damping coefficients of the substructures, using the limited absolute accelerations and the identified interface force above the substructure. Similarly, for the nonlinear substructure, UKF is used to identify the extended space including the displacements, velocities, stiffness, damping coefficients and control parameters for the hysteretic Bouc-Wen model and the force at the interface of substructures. Finally a 10-story shear-type structure with multiple inter-story hysteresis is used for numerical simulation and is identified using the decentralized approach, and the identified results are compared with those using only EKF or UKF for the complete structure identification. The results show that the decentralized approach has the advantage of more stability, relative less computation and higher estimation precision.

Citation Download Citation

Dongwang Tao, Hui Li, and Qiang Ma "Decentralized identification of nonlinear structure under strong ground motion using the extended Kalman filter and unscented Kalman filter", Proc. SPIE 9804, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, and Civil Infrastructure 2016, 980420 (22 April 2016); https://doi.org/10.1117/12.2218964

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