Intelligent Diagnosis of the Electrical Equipment Technical Condition

AbstractAn intelligent method of diagnosing the technical condition of electrical equipment and mechanical devices connected with it is described. The method is based on the combined use of fuzzy logic and neural networks. Fuzzy submodel determines the degree of development of each fault. The neural network determines the state of the object as a whole. The experimental study of the method for the diagnosis of a brushless DC motor and associated equipment at different speeds is presented. It was found that this method allows troubleshooting at any speed. The most informative rate equals half of the maximum. The fault detected in the experiment was confirmed during the inspection of electrical equipment