Expert system through a fuzzy logic approach for the macroscopic visual analysis of corroded metallic ferrous surfaces: Knowledge acquisition process

Abstract

Corrosion is one of main mechanisms of degradation in metallic materials. This article presents an expert system with fuzzy logic as a learning method for the visual analysis of ferrous metal surfaces. The procedure includes five input variables that represent the principal macroscopic visual variables of the proposed corrosion mechanisms for ferrous metal surfaces. This new method is intended as a support tool for experts in visual analysis of corrosive phenomena on ferrous metal surfaces.