AUTOMATED VISION SYSTEM FOR INSPECTION OF SURFACE CASTING DEFECTS BASED ON ADVANCED COMPUTER TECHNIQUES

A camera based machine vision system for the automatic inspection of surface defects in aluminum die casting has been developed. Depending on part design and processing techniques, castings may develop surface discontinuities such as cracks and pores that greatly influence the material's properties. Since the human visual inspection is slow and expensive, a computer vision system is an alternative solution for the online inspection. The developed vision system uses an advanced image processing algorithm based on modified Laplacian of Gaussian (LoG) edge detection method and advanced lighting system. The defect inspection algorithm consists of several parameters that allow the user to specify the sensitivity level at which he can accept the defects in the casting. In addition to the developed image processing algorithm, an advanced learning process has been developed, based on the methods of computational intelligence (artificial neural network). This process allows automatic selection and categorization of the measured defects, where three groups of defects were investigated: such as blowholes, shrinkage porosity and shrinkage cavity.