Ann Analysis of Wear Behaviour of Plasma Sprayed Iron Aluminide Coating
Keywords:
Neural Network, Solid particle erosion, Iron aluminide coating, Plasma SprayingAbstract
Intermetallic compounds find extensive use in high temperature structural applications. The Fe3Al based intermetallic alloys offer unique benefits of excellent oxidation and sulfidation resistance at a potential cost lower than many stainless steels. Plasma spraying is considered as a non-linear problem with respect to its variables: either materials or operating conditions. To obtain functional coating exhibiting selected in-service properties, combinations of processing parameters have to be planned. These combinations differ by their influence on the coating properties and characteristics. To control the spraying process, one must recognize the parameter interdependencies, correlations and individual effects on coating characteristics. This paper proposes a mathematical technique based on neural computations to study the effects of process variables on the wear behavior of iron-aluminide coatings made by plasma spraying. ANNs are excellent tools for complex processes that have many variables and complex interactions. The analysis is based on an Artificial Neural Network (ANN) taking into account training and test procedure to predict the dependence of erosion wear behavior on angle of impact and velocity of erodent. This technique helps in saving time and resources for experimental trials.
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