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Full-Field Vibration Response Estimation from Sparse Multi-Agent Automatic Mobile Sensors Using Formation Control

Debasish Jana1,2, Satish Nagarajaiah2,3

  • 1Samueli Civil and Environmental Engineering, University of California, Los Angeles, CA 90095, USA.

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|September 28, 2023
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Summary
This summary is machine-generated.

This study introduces an automated multi-agent mobile sensing framework for structural vibration response. The system uses formation control and compressive sensing to accurately map full-field structural vibrations, aiding in health monitoring.

Keywords:
compressive sensingformation controlfull-field sensingmobile sensorsmulti-agent systemstructural health monitoring

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Area of Science:

  • Engineering
  • Robotics
  • Signal Processing

Background:

  • Mobile sensors offer advantages for structural vibration sensing, providing dense spatial data.
  • Current methods often rely on manual driving or costly self-driving vehicles for data acquisition.
  • Automated solutions are needed to overcome limitations in current structural health monitoring (SHM) practices.

Purpose of the Study:

  • To develop and validate a formation control framework for automatic multi-agent mobile sensing in structural vibration analysis.
  • To enable efficient and cost-effective dense spatial information acquisition for SHM.
  • To estimate full-field vibration response using data from mobile sensors.

Main Methods:

  • A formation control algorithm was developed to manage multi-agent system behavior for sensing.
  • Vibration data from mobile sensors were used to estimate the structure's full-field response.
  • Compressive sensing in the spatial domain was applied to reconstruct the vibration response matrix.

Main Results:

  • The proposed formation control algorithm effectively guided multi-agent systems for structural response sensing.
  • Compressive sensing accurately reconstructed the dense full-field vibration response.
  • High reconstruction accuracy was achieved, demonstrating the framework's efficacy on a bridge model.

Conclusions:

  • The multi-agent mobile sensing framework offers a significant advancement for automated structural response measurement.
  • This approach has direct applicability to structural health monitoring and resilience assessment.
  • The study highlights the potential of coordinated mobile sensing for infrastructure evaluation.