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Damage detection on sudden stiffness reduction based on discrete wavelet transform.

Bo Chen1, Zhi-wei Chen2, Gan-jun Wang3

  • 1Key Laboratory of Roadway Bridge and Structural Engineering, Wuhan University of Technology, Wuhan 430070, China.

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Summary

This study introduces a new damage index to detect sudden stiffness reduction in structures. The index accurately identifies damage time, location, and severity using wavelet transform analysis of acceleration responses.

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Area of Science:

  • Structural Engineering
  • Vibration Analysis
  • Damage Detection

Background:

  • Sudden stiffness reduction in structures can cause signal discontinuity in acceleration responses.
  • Detecting such damage is crucial for structural health monitoring.
  • Existing methods may not effectively pinpoint the exact time and location of sudden stiffness changes.

Purpose of the Study:

  • To investigate damage detection methods for sudden stiffness reduction in building structures.
  • To develop a novel damage index for identifying damage time, location, and severity.
  • To assess the effectiveness and reliability of the proposed index under various conditions.

Main Methods:

  • Utilizing discrete wavelet transform to extract signal discontinuity from acceleration responses.
  • Proposing a new damage index based on the variation of wavelet detail coefficients.
  • Conducting numerical simulations on a five-story shear building with different excitations and damage levels.

Main Results:

  • The variation in first-level detail coefficients is linearly proportional to stiffness reduction magnitude.
  • The proposed damage index accurately detects the time, location, and severity of sudden stiffness changes.
  • The index's effectiveness is validated through simulations under various damage scenarios and noise levels.

Conclusions:

  • The developed damage index reliably identifies sudden structural damage events.
  • Accurate damage detection is achievable provided measurement noise intensity remains limited.
  • The method offers a promising approach for real-time structural health monitoring.