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Lamb Wave-Based Structural Damage Detection: A Time Series Approach Using Cointegration.

Phong B Dao1

  • 1Department of Robotics and Mechatronics, Faculty of Mechanical Engineering and Robotics, AGH University of Krakow, Al. Mickiewicza 30, 30-059 Krakow, Poland.

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Summary
This summary is machine-generated.

This study introduces a novel cointegration method for structural damage evaluation using Lamb wave data, overcoming limitations from complex propagation and temperature effects. The approach effectively detects and distinguishes damage conditions in structures, enhancing structural health monitoring.

Keywords:
Lamb wavesaluminium platecointegrationdamage detectionstructural health monitoringtemperature effecttime series analysis

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Area of Science:

  • Materials Science and Engineering
  • Mechanical Engineering
  • Non-destructive Testing

Background:

  • Lamb waves are widely used for structural damage detection but face practical limitations.
  • Challenges include complex wave propagation modes and temperature variations affecting measurements.
  • Existing methods struggle with direct interpretation of Lamb wave responses for structural health.

Purpose of the Study:

  • To propose a novel, two-step cointegration-based computational procedure for structural damage evaluation.
  • To utilize Lamb wave data represented as time series with common trends for damage assessment.
  • To develop a method robust to temperature fluctuations for improved structural health monitoring (SHM).

Main Methods:

  • A two-step cointegration analysis procedure is employed.
  • Lamb wave time series are grouped based on common temperature trends.
  • Cointegration analysis is applied to each group, creating damage-specific models.
  • Geometrical and statistical features (shape, amplitude, variance) of series and residuals are extracted for damage detection.

Main Results:

  • The cointegration approach successfully detects and distinguishes between undamaged and damaged states.
  • The method was validated using Lamb wave data from aluminium plates under temperature fluctuations.
  • The proposed technique demonstrates effectiveness in handling environmental variations like temperature changes.

Conclusions:

  • The novel cointegration-based method offers a robust solution for Lamb wave-based damage detection.
  • This approach effectively addresses limitations posed by complex wave modes and temperature variations.
  • The methodology is applicable to various SHM systems dealing with data exhibiting common environmental or operational trends.