Stone impact damage to automotive paint finishes—A statistical and neural net analysis of electrochemical impedance data

Abstract

Automotive car bodies are subject to impact by stones either lofted from tires or launched by other passing vehicles. Impact can result either in physical loss of paint or the possibility of failure at the metal/phosphate—polymer interface. Corrosion brought about as a result of impact is referred to as Impact Induced Corrosion or IIC. Electrochemical impedance is very sensitive to delamination at the metal—polymer interface and is able to discern the influence of velocity, angle of impact, the type of coating and ambient temperature on stone impact damage. Application of both statistical and Artificial Neural Network (ANN) analysis are presented.