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Accurate structural health monitoring requires synchronized data from multiple data acquisition systems (DAS). This study introduces a system identification algorithm to correct time synchronization errors in ambient vibration data, ensuring reliable structural dynamic characterization.

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Area of Science:

  • Civil Engineering
  • Structural Health Monitoring
  • System Identification

Background:

  • Output-only modal analysis is crucial for structural health monitoring.
  • Multiple data acquisition systems (DAS) are often necessary for comprehensive measurements.
  • Time synchronization issues between DAS can lead to inaccurate structural dynamic characterization.

Purpose of the Study:

  • To propose a system-identification-based time synchronization algorithm for output-only modal analysis using multiple DAS.
  • To address and correct time synchronization discrepancies in ambient vibration data.

Main Methods:

  • A novel procedure compensating for phase angle shifts to identify time synchronization issues.
  • Application of the kernel density function to enhance algorithm robustness against data inconsistencies.
  • Validation using artificially de-synchronized data from a full-scale bridge and real-world data from a 30-story building.

Main Results:

  • The proposed algorithm effectively identifies and corrects time synchronization errors in multi-DAS ambient vibration data.
  • Demonstrated proof of concept on a de-synchronized bridge dataset.
  • Successful synchronization of data from a 30-story building where previous attempts failed.

Conclusions:

  • The developed algorithm provides a reliable solution for time synchronization problems in multi-DAS output-only modal analysis.
  • Accurate synchronization is essential for dependable structural health monitoring.
  • The method enhances the accuracy and reliability of structural dynamic characterization.