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Diagnostic model for mechanical wear state based on fuzzy neural network and its application

An intelligent diagnostic model for mechanical wear state based on a fuzzy neural network is proposed. The model can handle input features presented in quantitative and/or linguistic form and classify patterns in terms of fuzzy class membership values. This allows efficient modeling of fuzzy diagnosis of mechanical wear state in terms of the Ferrogram Analysis Report Sheet. The application of the model to the diagnosis of wear state of diesel engines is demonstrated. The results are very satisfactory.