Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Damage Identification of Frame Structures with Joint Damage under Earthquake Excitation
Previous damage detection of frame structures mainly focuses on the detection of beam and column element damage. It has been shown that beam-column joints in frame structures are more susceptible to damage than the other members in the structure. Joint damage may be represented by the reduction of beam-column connection rigidity. Therefore, damage detection of a frame structure with joint damage includes the identification of joint connection stiffness in additional to those of beam and column stiffness, which involves the difficulty of identifying a large number of unknown structural parameters. In this paper, an algorithm based on a two-step Kalman filter approach is presented for the damage detection of frame structures with joint damage under earthquake excitation using partial measurements of structural acceleration responses. Recursive solutions for unknown structural parameters and structural state vector are derived by a two-step Kalman filter, respectively. Therefore, the number of unknown variables to be estimated in each step is reduced compared with the conventional Extended Kalman filter (EKF) approach. Structural damage is detected from the degradation of the identified stiffness values of joints, beam and column elements of frame structures. A numerical example and a lab experiment test data are used to validate the performances of the proposed algorithm for damage identification of various joint damage scenarios in frame structures under earthquake excitation.
Damage Identification of Frame Structures with Joint Damage under Earthquake Excitation
Previous damage detection of frame structures mainly focuses on the detection of beam and column element damage. It has been shown that beam-column joints in frame structures are more susceptible to damage than the other members in the structure. Joint damage may be represented by the reduction of beam-column connection rigidity. Therefore, damage detection of a frame structure with joint damage includes the identification of joint connection stiffness in additional to those of beam and column stiffness, which involves the difficulty of identifying a large number of unknown structural parameters. In this paper, an algorithm based on a two-step Kalman filter approach is presented for the damage detection of frame structures with joint damage under earthquake excitation using partial measurements of structural acceleration responses. Recursive solutions for unknown structural parameters and structural state vector are derived by a two-step Kalman filter, respectively. Therefore, the number of unknown variables to be estimated in each step is reduced compared with the conventional Extended Kalman filter (EKF) approach. Structural damage is detected from the degradation of the identified stiffness values of joints, beam and column elements of frame structures. A numerical example and a lab experiment test data are used to validate the performances of the proposed algorithm for damage identification of various joint damage scenarios in frame structures under earthquake excitation.
Damage Identification of Frame Structures with Joint Damage under Earthquake Excitation
Lei, Ying (Autor:in) / Li, Qing (Autor:in) / Chen, Feng (Autor:in) / Chen, Zhiwei (Autor:in)
Advances in Structural Engineering ; 17 ; 1075-1087
01.08.2014
13 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Damage Identification of Frame Structures with Joint Damage under Earthquake Excitation
British Library Conference Proceedings | 2014
|Damage Identification of Frame Structures with Joint Damage under Earthquake Excitation
Online Contents | 2014
|Studies of Joint Damage Identification for Frame Structures
British Library Conference Proceedings | 2007
|Damage Assessment of RC Frame Structures under Multi-Earthquake Sequences
Tema Archiv | 2012
|Damage Assessment of RC Frame Structures under Multi-Earthquake Sequences
British Library Conference Proceedings | 2012
|