A robust poly-reference frequency-domain identification method to extract dynamic properties from vibration data.

Area of Science:

• Structural Dynamics and Vibration Analysis
• Computational Mechanics
• Experimental Modal Analysis

Background:

• Extracting dynamic properties from structural vibration tests is crucial for system analysis.
• Existing methods often struggle with accuracy and robustness, particularly when dealing with noise-contaminated data.
• A need exists for improved techniques in experimental modal analysis.

Purpose of the Study:

• To propose a novel, robust, and accurate frequency-domain method for extracting dynamic properties from vibration data.
• To enhance the identification of modal parameters in structural systems.
• To address limitations of current methods when applied to noisy vibration measurements.

Main Methods:

• Development of a frequency-domain modal model for dynamic property extraction.
• Application and validation of the proposed method on simulated (finite element model) and experimental vibration data.
• Performance assessment using stabilization diagrams, relative error analysis, Modal Assurance Criterion (MAC), and frequency response function synthesis.

Main Results:

• The proposed method demonstrated superior clarity and accuracy in identifying dynamic properties compared to state-of-the-art techniques.
• Effective application across diverse scenarios, including simulated data and real-world structures (platform specimen, heritage court building).
• Consistent performance improvement observed across various validation metrics.

Conclusions:

• The developed frequency-domain method offers a robust and accurate solution for extracting dynamic properties from vibration tests.
• This approach significantly enhances the reliability of modal parameter identification, especially in the presence of measurement noise.
• The findings suggest a valuable advancement for structural health monitoring and system identification applications.