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Cortical Bone Assessment Using Ultrasonic Guided Waves: A Reproducibility Study in a Healthy Population
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Methodology for Detecting Progressive Damage in Structures Using Ultrasound-Guided Waves.

Gerardo Aranguren1, Javier Bilbao2, Josu Etxaniz1

  • 1Department of Electronic Technology, Faculty of Engineering of Bilbao, University of the Basque Country (UPV/EHU), 48013 Bilbao, Spain.

Sensors (Basel, Switzerland)
|February 26, 2022
PubMed
Summary
This summary is machine-generated.

This study presents novel equipment and algorithms for detecting progressive corrosion damage in aircraft structures using ultrasonic guided waves. The developed system enables onboard monitoring and scalable damage assessment, improving structural health monitoring capabilities.

Keywords:
SHMcorrosionpattern matchingpattern recognitionpiezoelectric transducers

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Area of Science:

  • Materials Science
  • Mechanical Engineering
  • Aerospace Engineering

Background:

  • Structural health monitoring (SHM) is crucial for metallic and composite structures.
  • Current commercial SHM devices lack onboard installation and scalability.
  • Detecting progressive damage like corrosion requires advanced sensor technology and algorithms.

Purpose of the Study:

  • To introduce self-developed equipment for generating ultrasonic guided waves.
  • To present a methodology for detecting progressive corrosion damage in aircraft structures.
  • To develop algorithms for monitoring damage trends.

Main Methods:

  • Utilized an array of 10 piezoelectric transducers with a custom SHM ultrasonic system.
  • Simulated accelerated corrosion using aluminum and carbon-reinforced polymer plates with seawater over eight weeks.
  • Employed hardware algorithms, pattern matching, and pattern recognition for data processing.

Main Results:

  • Generated 100 waveforms per test, with hardware pre-processing to minimize data.
  • Successfully monitored progressive corrosion damage over an eight-week experimental period.
  • Extracted information on corrosion degree through three distinct processing stages.

Conclusions:

  • The proposed methodology effectively detects trends in progressive structural degradation.
  • The self-developed equipment and algorithms offer a scalable solution for onboard SHM.
  • This approach enhances the capability for monitoring corrosion damage in aircraft structures.