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Structural Response Reconstruction Based on Experimental Approximation and Model Reduction

  • Jinsong Yang
  • , Yidan Liu
  • , Xuandong Lu*
  • , Tiantian Wang
  • , Jingsong Xie
  • , Jingjing He
  • *此作品的通讯作者
  • Central South University

科研成果: 期刊稿件文章同行评审

摘要

Model-driven response reconstruction is widely applied to supplement inaccessible dynamic information in mechanical structural health monitoring. However, increasing complexity of structures with considerable degrees of freedom and nonshareability of substructures based on security issues make it inefficient, even impossible, to perform response reconstruction. To overcome these difficulties, a reconstruction strategy is presented by innovatively incorporating experimental approximation and model reduction. As the baseline of response reconstruction, the complete structural FEM is integrated by the defined FEM-based substructures (FSs) and experiment-based substructures (ESs). On one hand, FS aims to deal with low reconstruction efficiency and is transformed from the accessible substructure by the Crag–Bampton method that eliminates redundant matrix data when ensuring accuracy. On the other hand, ES is established to improve the condition of modeling difficulty that inaccessible FEM of local components is replaced by the approximate model, whose vibration characteristics are described through removing a predesigned fixture using experimental coupling measurement. The complete model is established by assembling the above substructures at the desired interface. Response reconstruction referred to the area of ES is realized through transferring frequency response functions among substructures. Otherwise, reconstruction could be directly accomplished by Eigen solution and inverse modal transformation. Response reconstruction cases of a numerical beam structure and an experimental flange-tube assembly are applied to verify superiority and accuracy of the proposed method.

源语言英语
文章编号5553171
期刊Structural Control and Health Monitoring
2026
1
DOI
出版状态已出版 - 2026

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