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Bridge Damage Identification Using Vehicle Bump Based on Additional Virtual Masses.

Qingxia Zhang1, Jilin Hou2, Łukasz Jankowski3

  • 1School of Civil Engineering, Dalian Minzu University, Dalian 116600, China.

Sensors (Basel, Switzerland)
|January 16, 2020
PubMed
Summary

This study introduces a novel bridge damage identification method using a vehicle bump as excitation and additional virtual mass. The technique accurately detects structural damage even with noise, overcoming limitations of traditional monitoring methods.

Keywords:
additional virtual massbridgedamage identificationstructural health monitoringvehicle bump

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Area of Science:

  • Structural Engineering
  • Bridge Health Monitoring
  • Vibrational Analysis

Background:

  • Accurate structural damage identification is crucial for bridge health monitoring.
  • Limitations in measurement points and data hinder damage detection in large-scale structures.
  • Existing methods often struggle with real-world complexities and potential overloading.

Purpose of the Study:

  • To develop a robust damage identification method for bridges utilizing vehicle-induced excitation.
  • To address the challenge of insufficient structural response data in bridge monitoring.
  • To propose a technique that avoids overloading bridges while enhancing modal information.

Main Methods:

  • Derivation of general equations for virtual modifications (mass, stiffness, damping).
  • Formulation of a damage identification method based on additional virtual mass.
  • Detailed analysis and estimation of vehicle bump-induced excitation.
  • Construction of frequency responses for a virtual structure with added virtual mass.

Main Results:

  • The proposed additional virtual mass method enables accurate damage identification.
  • The method effectively utilizes vehicle bump excitation and acceleration responses.
  • Numerical simulations demonstrated successful damage detection even with 15% Gaussian random noise.

Conclusions:

  • The vehicle bump-induced additional virtual mass method is a viable approach for bridge damage identification.
  • This technique enhances modal information for accurate detection without overloading the structure.
  • The method shows promise for improving the health monitoring of in-service bridges.