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Structural damage identification based on recursive proper orthogonal decomposition and strong tracking extended Kalman filtering
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Shaochong YANG1, 2, Yuan YAO1, 2, Jialiang LIU1, 2, Zhen LEI1, 2, Youliang FANG1, 2
Journal of Vibration Engineering | 2025, 38(1) : 117 - 125
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Journal of Vibration Engineering | 2025, 38(1): 117-125
Structural damage identification based on recursive proper orthogonal decomposition and strong tracking extended Kalman filtering
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Shaochong YANG1, 2, Yuan YAO1, 2, Jialiang LIU1, 2, Zhen LEI1, 2, Youliang FANG1, 2
Affiliations
  • 1.College of Civil Engineering and Architecture, Hebei University, Baoding 071002, China
  • 2.Technology Innovation Center for Testing and Evaluation in Civil Engineering of Hebei Province, Baoding 071002, China
Published: 2025-01-10 doi: 10.16385/j.cnki.issn.1004-4523.2025.01.013
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Aiming at the problem that the existing damage identification methods are difficult to track the structural damage in real time and require a large amount of calculation, a model order reduction and online damage identification method based on the combination of recursive proper orthogonal decomposition (RPOD) and strong tracking extended Kalman filter (STEKF) is proposed.The structural damage identification under dynamic load is studied. The RPOD method is used to update online and construct the reduced-order model reflecting the structure state in real time, which solves the problem of large calculation and difficult convergence of dynamic analysis of multi-degree of freedom structures under unknown loads. Meanwhile, the evolution of damage is tracked and located. The STEKF method is used to track the state vector of the reduced-order model and identify the reduced-order model parameters degraded by damage. The feasibility of the proposed method is verified by numerical simulation of a six-story shear frame and model test of a three-story steel frame. The results show that the proposed method can accurately construct the reduced-order model and track the time-varying history of the reduced-order model parameters. Meanwhile, it can effectively identify the location and extent of the damage of the shear building structure, even when dealing with high levels of noise, it retains high accuracy.

damage identification  /  reduced-order modeling  /  recursive proper orthogonal decomposition (RPOD)  /  strong tracking extended Kalman filter (STEKF)  /  data driven
Shaochong YANG, Yuan YAO, Jialiang LIU, Zhen LEI, Youliang FANG. Structural damage identification based on recursive proper orthogonal decomposition and strong tracking extended Kalman filtering[J]. Journal of Vibration Engineering, 2025 , 38 (1) : 117 -125 . DOI: 10.16385/j.cnki.issn.1004-4523.2025.01.013
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Year 2025 volume 38 Issue 1
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Article Info
doi: 10.16385/j.cnki.issn.1004-4523.2025.01.013
  • Receive Date：2023-02-25
  • Online Date：2026-02-11
  • Published：2025-01-10
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  • Received：2023-02-25
  • Revised：2023-04-23
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Affiliations
    1.College of Civil Engineering and Architecture, Hebei University, Baoding 071002, China
    2.Technology Innovation Center for Testing and Evaluation in Civil Engineering of Hebei Province, Baoding 071002, China
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