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Updated: Dec 22, 2025

Crack Monitoring in Resonance Fatigue Testing of Welded Specimens Using Digital Image Correlation
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Crack Detection Zones: Computation and Validation.

Simon Pfingstl1, Martin Steiner1, Olaf Tusch2

  • 1Laboratory for Product Development and Lightweight Design, Technical University of Munich, Boltzmannstr. 15, 85748 Garching, Germany.

Sensors (Basel, Switzerland)
|May 6, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a method to minimize strain sensors for aerospace structural health monitoring. It identifies optimal sensor positions to detect fatigue damage early, reducing inspection costs and effort.

Keywords:
aerospace structurescrack detectionfatigue damagepredictive maintenancestructural health monitoring

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Area of Science:

  • Aerospace Engineering
  • Materials Science
  • Structural Health Monitoring

Background:

  • Aerospace structures undergo extensive fatigue testing to detect failures.
  • Current inspection methods are labor-intensive and costly.
  • Strain sensor data can potentially reduce inspection efforts.

Purpose of the Study:

  • To minimize the number of strain sensors required for detecting fatigue-induced damage.
  • To optimize sensor positioning for effective structural health monitoring.
  • To reduce the cost and effort associated with sensor deployment in aerospace structures.

Main Methods:

  • Establishing a detection criterion based on the relative change of strain amplitudes under cyclic loading.
  • Exploring the space of possible crack lengths to define 'detection zones'.
  • Demonstrating the approach on a representative airplane lower wing section.

Main Results:

  • The proposed method enables the detection of fatigue-induced damage before complete failure.
  • A single strategically placed strain sensor can monitor multiple fatigue-critical spots.
  • Four fatigue-critical spots on a wing structure were monitored with one sensor.

Conclusions:

  • The developed method allows for reliable structural health monitoring with a minimal number of sensors.
  • Optimized sensor placement is crucial for effective fatigue damage detection.
  • The findings can significantly reduce inspection costs and improve safety in aerospace applications.