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NEURAL NETWORK ANALYSIS FOR SLIDING WEAR OF 13%CR STEEL COATINGS BY ELECTRIC ARC SPRAYING | ||
| DIYALA JOURNAL OF ENGINEERING SCIENCES | ||
| Article 21, Volume 3, Issue 0, 2010, Pages 157-169 PDF (0 K) | ||
| Author | ||
| Ali Khudhair | ||
| Abstract | ||
| ABSTRACT:- Artificial Neural Networks (ANNs) are a new type of information processing technique based on modeling the neural systems of human brain. The potential of using neural networks in prediction of wear rate quantities of 13%Cr steel coating produced by arc spraying, has been studied in the present work. The material is subjected to dry sliding wear test using pin-on-ring apparatus at room conditions. Effects of normal load, sliding speed and time on wear rate have been investigated by using artificial neural networks. The experimental results were used to train ANN model successfully with accepted mean square error (MSE) of 0.00077504. The ANN predictions shows very good agreement with experimental values with correlation coefficient of 0.99778, thus ANN can be considered excellent tool for modeling complex processes that have many variables. Keywords:- Artificial Neural Network; Wear; Coating | ||
| Keywords | ||
| artificial neural network; Wear; Coating | ||
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