Development and implementation of image-based algorithms for measurement of deformations in material testing

Area of Science:

• Civil Engineering
• Materials Science
• Computer Vision

Background:

• Traditional sensors in construction material testing have limitations in scope and cost.
• Structural engineers require advanced methods for accurate deformation and crack analysis.
• Digital image processing offers potential for enhanced material testing.

Purpose of the Study:

• To develop and implement three novel image-based methods for point displacement detection and measurement.
• To create tools for crack measurement in fiber-reinforced specimens and 2D/3D deformation analysis.
• To validate the accuracy and utility of these methods compared to traditional sensors.

Main Methods:

• Development of three specialized image-based tools utilizing advanced image processing algorithms.
• Implementation of software for automated crack measurement and 2D/3D deformation analysis.
• Testing and validation through simulations and real-world laboratory applications on construction materials.

Main Results:

• Successful implementation of image-based methods for detecting and measuring displacements of numerous points.
• Demonstrated accuracy of the developed software through comparisons with traditional laboratory sensors.
• Showcased potential for automation, cost reduction, and expanded analytical capabilities in material testing.

Conclusions:

• The developed image-based methods provide accurate and extensive analysis for construction material testing.
• These tools offer a cost-effective and automated alternative or supplement to traditional sensors.
• The research facilitates new possibilities for detailed deformation and crack analysis in laboratory settings.