Machine Vision-Based Fatigue Crack Propagation System

Area of Science:

• Materials Science
• Mechanical Engineering
• Computer Vision

Background:

• Fatigue cracks in components initiate at stress concentration points on surfaces.
• Traditional methods like strain gauge sensors are often costly and complex.
• Monitoring crack propagation is crucial for structural integrity and safety.

Purpose of the Study:

• To introduce a cost-effective machine vision system for detecting fatigue crack propagation.
• To propose an alternative to strain gauge sensor-based measurements.
• To demonstrate the implementation and performance of the developed system.

Main Methods:

• Development of a machine vision system utilizing an industrial camera.
• Integration with specialized software for image processing and analysis.
• Application of the system to samples exhibiting fatigue crack propagation.

Main Results:

• Successful implementation of the machine vision system.
• Demonstration of the system's capability to detect and monitor fatigue crack propagation.
• Validation of the system's outputs against crack propagation samples.

Conclusions:

• The machine vision system offers a promising low-cost solution for fatigue crack detection.
• The system provides a viable alternative to conventional strain gauge methods.
• Further application in industrial settings for monitoring component fatigue is suggested.