fatigue damage evaluation by image processing from surface feature for aluminum 2024-T351 alloy

This article presents a methodology for the experimental analysis of fatigue using digital image processing techniques. This methodology consists of a computer vision system that integrates the digital image and processing techniques on- line using special programming routines. The low-cycle fatigue behavior of aluminum 2024 alloy under different strain range would be investigated at room temperature. In addition, relationship between the surface features in the low-cycle fatigue test and the fatigue life of this alloy are investigated by image processing. The image-processed photographs of the surface of the specimen tested at a total strain range is performed and feature point that define for the pixels. Then feature point changes are investigated during the low cycle fatigue test and relationship between these changes and fatigue life as a criterion is considered to be for fatigue assessment

Keywords:

low cycle fatigue , image processing , surface feature , fatigue life , aluminum 2024 alloy