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Updated: Nov 20, 2025

Crack Monitoring in Resonance Fatigue Testing of Welded Specimens Using Digital Image Correlation
Published on: September 29, 2019
Detection and tracking of cracks based on thermoelastic stress analysis
C A Middleton1, M Weihrauch1, W J R Christian1
1School of Engineering, University of Liverpool, The Quadrangle, Brownlow Hill, Liverpool L69 3GH, UK.
A new method uses image decomposition to analyze thermoelastic stress, enabling early detection of cracks as small as 1 mm. This advance in structural health monitoring utilizes low-cost sensors for improved crack detection and tracking.
Area of Science:
- Materials Science
- Mechanical Engineering
- Non-Destructive Testing
Background:
- Thermoelastic stress analysis is promising for structural health monitoring.
- Low-resolution sensors and complex loading conditions pose challenges for traditional data evaluation.
- Existing methods struggle with precise crack detection and tracking.
Purpose of the Study:
- To develop an alternative method for evaluating thermoelastic stress data from low-cost sensors.
- To enable accurate detection and tracking of crack initiation and propagation.
- To advance structural health monitoring capabilities using cost-effective sensors.
Main Methods:
- Image decomposition to generate feature vectors characterizing the thermoelastic effect.
- Data collection using photovoltaic and microbolometer detectors under various loading conditions.
- Calculating Euclidean distance between feature vectors to detect damage.
Main Results:
- Successfully detected and tracked cracks as small as 1 mm.
- Identified an increase in the rate of change of Euclidean distance indicating critical crack propagation.
- Demonstrated the effectiveness of the differential feature vector method with low-cost sensors.
Conclusions:
- The differential feature vector method offers a substantial advancement for monitoring crack initiation and propagation.
- This technology is suitable for both structural testing and in-service monitoring.
- Low-cost sensors can be effectively utilized for precise structural health monitoring.
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