FUZZY LOGIC COUPLED WITH PERIDYNAMICS FOR IMAGE PROCESSING TO DETECT CRACKS IN RAILS
Cihan Mizrak Erdogan Madenci Yusuf Yurekli Fatih Pehlivan
AbstractRailways require high investment costs and need continuous and controlled monitoring for defects on the surface and inside the rail material. The existing nondestructive methods for crack detection are commonly based image processing. This study provides a comparison of the existing methods, and presents a new method to detect cracks also based on image processing. The present approach utilizes the fuzzy logic coupled with the peridynamic differential operator. Its robustness is demonstrated by detecting cracks in an image of a rail with cracks.