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Multivariate empirical mode decomposition-based structural damage localization using limited sensors.

Sandeep Sony1, Ayan Sadhu1

  • 1Department of Civil and Environmental Engineering, Western University, Canada.

Journal of Vibration and Control : JVC
|July 18, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces multivariate empirical mode decomposition (MEMD) for pinpointing structural damage using minimal sensor data. The novel method effectively identifies minor damage, even with few measurements, enabling cost-effective structural health monitoring.

Keywords:
Structural health monitoringdamage indexdamage localizationlimited sensorsmultivariate empirical mode decomposition

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Area of Science:

  • Structural Engineering
  • Vibrational Analysis
  • Signal Processing

Background:

  • Accurate damage localization is crucial for structural integrity.
  • Existing methods often require extensive sensor networks or struggle with minor damage detection.

Purpose of the Study:

  • To propose a novel method for structural damage localization using limited measurements.
  • To enhance the cost-effectiveness of structural health monitoring.

Main Methods:

  • Utilized multivariate empirical mode decomposition (MEMD) to decompose acceleration responses into mono-component modal responses.
  • Evaluated modal energy and proposed a damage localization feature based on modal energy differences.
  • Determined a threshold for damage identification and validated sensor locations.

Main Results:

  • Successfully validated the proposed MEMD method through numerical and full-scale studies.
  • Demonstrated feasibility with limited measurement cases, highlighting cost-effectiveness.
  • Achieved detection of as little as 2% change in global modal parameters, outperforming existing time-frequency methods.

Conclusions:

  • The MEMD-based approach offers a robust and sensitive method for structural damage localization.
  • The technique is effective even with a reduced number of sensors, supporting practical structural health monitoring applications.