Buy article PDF
Instant access to
the full article PDF
for the next 48 hrs
US$ 35
|
Smart Structures and Systems Volume 12, Number 6, December 2013 , pages 619-640 DOI: https://doi.org/10.12989/sss.2013.12.6.619 |
|
|
|
Substructure based structural damage detection with limited input and output measurements |
||
Y. Lei, C. Liu, Y.Q. Jiang and Y.K. Mao
|
||
| Abstract | ||
| It is highly desirable to explore efficient algorithms for detecting structural damage of large size structural systems with limited input and output measurements. In this paper, a new structural damage detection algorithm based on substructure approach is proposed for large size structural systems with limited input and output measurements. Inter-connection effect between adjacent substructures is treated as \"additional unknown inputs\" to substructures. Extended state vector of each substructure and its unknown excitations are estimated by sequential extended Kalman estimator and least-squares estimation, respectively. It is shown that the \"additional unknown inputs\" can be estimated by the algorithm without the measurements on the substructure interface DOFs, which is superior to previous substructural identification approaches. Also, structural parameters and unknown excitation are estimated in a sequential manner, which simplifies the identification problem compared with other existing work. Structural damage can be detected from the degradation of the identified substructural element stiffness values. The performances of the proposed algorithm are demonstrated by several numerical examples and a lab experiment. Measurement noise effect is considered. Both the simulation results and experimental data validate that the proposed algorithm is viable for structural damage detection of large size structural systems with limited input and output measurements. | ||
| Key Words | ||
| structural identification; structural damage detection; substructure approach; extended Kalman estimator; least- squares estimation; unknown inputs | ||
| Address | ||
| Y. Lei: Department of Civil Engineering, Xiamen University, Xiamen 361005, China; State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China Y. Lei, C. Liu, Y.Q. Jiang and Y.K. Mao : Department of Civil Engineering, Xiamen University, Xiamen 361005, China | ||