AUTOMATED AISI 317L SS THIN SECTION IMAGE POROSITY RECOGNITION AND SEMI-AUTOMATED PRIORITIZATION FOR PREDICTING THE YIELDING POSITION BY MEANS OF IMAGE PROCESSING

Porosity is a common phenomenon in fabricated parts, which cause stress concentration and leads to yielding, brittle fraction fatigue of structures makes porosity recognition analyzing very important increase efficiency decrease the defects manufactured parts. Many researches have been done order detecting recognizing pores material by different numerical experimental methods. In this paper, an algorithm developed detect thin section images automatically prioritize them for semi-automatically prediction yielding position. The results following parameters porous material: number pores, position size maximum minimum distances both from each other boundaries. shows accuracy 83% simulated finite element method (FEM) tensile tests, creditable be used as non-destructive testing method.