Some thoughts on neural network modelling of microabrasion–corrosion processes

• Autor(a) principal: Mathew, M. T.
• Data de Publicação: 2008
• Outros Autores: Pai, P. S., Stack, M. M., Rocha, L. A.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/1822/8617
• topic: Tribocorrosion; microabrasion-corrosion process; artificial neural network (ANN); multilayer perceptron (MLP); radial basis function (RBF); resource allocation network; Science & Technology

There is increasing interest in the interactions of microabrasion, involving small particles of less than 10 mm in size, with corrosion. This is because such interactions occur in many environments ranging from the offshore to health care sectors. In particular, microabrasion–corrosion can occur in oral processing, where the abrasive components of food interacting with the acidic environment, can lead to degradation of the surface dentine of teeth. Artificial neural networks (ANNs) are computing mechanisms based on the biological brain. They are very effective in various areas such as modelling, classification and pattern recognition. They have been successfully applied in almost all areas of engineering and many practical industrial applications. Hence, in this paper an attempt has been made to model the data obtained in microabrasion–corrosion experiments on polymer/steel couple and a ceramic/lasercarb coating couple using ANN. A multilayer perceptron (MLP) neural network is applied and the results obtained from modelling the tribocorrosion processes will be compared with those obtained from a relatively new class of neural networks namely resource allocation network.