Damage detection in bilinear plane stress plates using the characteristic parameter method

The residual force vector method is commonly used for damage identification in truss structures but faces challenges when applied to planar plate elements due to their numerous characteristic parameters. To overcome this limitation, an improved method based on multi-characteristic parameter decomposition is proposed for damage identification in complex structural components. The method involves the following key steps: (1) decomposing the matrix element into eigenvalues to simplify the analysis, (2) calculating the stiffness connection matrix using the coordinate relationships of the structure, and (3) determining the damage location and severity by utilizing the damage location matrix and the element eigenvalues. The application of this improved method to a practical example demonstrates its effectiveness in accurately identifying damage, highlighting its potential for real-world structural health monitoring.

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Publication Details

Journal
AIP Advances
Published
2025-03-01
DOI
https://doi.org/10.1063/5.0254116
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Damage detection in bilinear plane stress plates using the characteristic parameter method

Y.Z. Chen, Zheng Kang
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AIP Advances
Structural Health Monitoring Techniques
article

Damage detection in bilinear plane stress plates using the characteristic parameter method

Y.Z. Chen, Zheng Kang
article en

Abstract

The residual force vector method is commonly used for damage identification in truss structures but faces challenges when applied to planar plate elements due to their numerous characteristic parameters. To overcome this limitation, an improved method based on multi-characteristic parameter decomposition is proposed for damage identification in complex structural components. The method involves the following key steps: (1) decomposing the matrix element into eigenvalues to simplify the analysis, (2) calculating the stiffness connection matrix using the coordinate relationships of the structure, and (3) determining the damage location and severity by utilizing the damage location matrix and the element eigenvalues. The application of this improved method to a practical example demonstrates its effectiveness in accurately identifying damage, highlighting its potential for real-world structural health monitoring.

AIP AdvancesVol. 15(3)
Shijiazhuang Tiedao University (CN)
Science and Technology Projects of Fujian Province
Openalex Percentile: Top 95%
Structural Health Monitoring Techniques
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