Reconstruction of composite panel deformation based on modal superposition and calibration method by fiber optic sensors

Accurately and promptly acquiring the structural morphological characteristics of aerospace panel structures is of great significance for achieving spacecraft attitude control and vibration suppression. To address this, this paper proposes a method for reconstructing the shape of composite panel, which combines the modal superposition method with a modal parameter calibration method (MSM-MPC). First, a modal matrix calibration method based on the least squares algorithm was developed to establish the mapping relationship between the strain and modal shapes of the tested structure. This approach resolves the deviations in the strain/displacement modal matrices caused by inaccuracies in the simulation-based mechanical model. Second, through a composite load excitation calibration method, the modal coordinates corresponding to each order of modal shapes of the tested structure were determined. This breakthrough eliminates the conventional modal superposition method’s reliance on simulation-based mechanical models to calculate modal coordinates, effectively reducing the impact of the simulation model on the accuracy of structural shape reconstruction. To validate the reconstruction effectiveness, numerical simulation results were used for validation, and a system for monitoring and reconstructing the shape of composite structures based on high-spatial-resolution distributed fiber optic sensors was developed. Research shows that the shape reconstruction effect of composite panel based on the MSM-MPC is significantly better than that of the conventional modal superposition method, demonstrating good engineering applicability.

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Published
2025-05-20
DOI
https://doi.org/10.1117/12.3059365
Citations
1
Primary Topic
Advanced Measurement and Detection Methods
Type
article
Field-Weighted Citation Impact
0.73
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Reconstruction of composite panel deformation based on modal superposition and calibration method by fiber optic sensors

Shoufeng Tang, Shiao Wang, Shiyang Liu, Jie Zeng et al.
1 citations
Advanced Measurement and Detection Methods
0.73
article

Reconstruction of composite panel deformation based on modal superposition and calibration method by fiber optic sensors

Shoufeng Tang, Shiao Wang, Shiyang Liu, Jie Zeng, Yiming Huang, Jinpeng Cui, Fan Shao
article en
1 citations

Abstract

Accurately and promptly acquiring the structural morphological characteristics of aerospace panel structures is of great significance for achieving spacecraft attitude control and vibration suppression. To address this, this paper proposes a method for reconstructing the shape of composite panel, which combines the modal superposition method with a modal parameter calibration method (MSM-MPC). First, a modal matrix calibration method based on the least squares algorithm was developed to establish the mapping relationship between the strain and modal shapes of the tested structure. This approach resolves the deviations in the strain/displacement modal matrices caused by inaccuracies in the simulation-based mechanical model. Second, through a composite load excitation calibration method, the modal coordinates corresponding to each order of modal shapes of the tested structure were determined. This breakthrough eliminates the conventional modal superposition method’s reliance on simulation-based mechanical models to calculate modal coordinates, effectively reducing the impact of the simulation model on the accuracy of structural shape reconstruction. To validate the reconstruction effectiveness, numerical simulation results were used for validation, and a system for monitoring and reconstructing the shape of composite structures based on high-spatial-resolution distributed fiber optic sensors was developed. Research shows that the shape reconstruction effect of composite panel based on the MSM-MPC is significantly better than that of the conventional modal superposition method, demonstrating good engineering applicability.

China University of Mining and Technology (CN), Nanjing University of Aeronautics and Astronautics (CN)
Sustainable cities and communities
Openalex Percentile: Top 28%
Advanced Measurement and Detection Methods
0.73
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