Robust and efficient modal identification framework for dense vision data based on spatial sampling consistency

Guangxian Li

doi:10.1016/j.jsv.2026.119961

Robust and efficient modal identification framework for dense vision data based on spatial sampling consistency

2026-06-17

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DOI：10.1016/j.jsv.2026.119961

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Abstract

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• Spatial sampling consistency of physical mode is used for robust identification. • Dynamic modal decomposition is used for efficient generation of candidate modes. • A two-stage clustering strategy is designed for automatic physical mode clustering. • Modal analysis tests are conducted on a thin-plate and a pre-twisted blade.

Keywords:

Modal identification

Spatial sampling consistency

Vision-based techniques

Dynamic mode decomposition

Two-stage clustering

Robust and efficient modal identification framework for dense vision data based on spatial sampling consistency

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