Kuznetsov D. Information technology for diagnostics group of asynchronous motors using spectral characteristics and intellectual classification

Object of study - the development, management and use of information about the state of induction motors methods and means of spectral diagnostics. Purpose - to develop information technology for the group diagnostics of induction motors based on an intelligent decision support system computer (DSSC) using spectral analysis and unit neural networks. Methods: range-current method; unit neural networks; method of fast Fourier transform; simulation methods; evolutionary method; methods and principles of object-oriented programming. Novelty - first proposed information technology to build an automated system of technical diagnostics group of induction motors; further developed a method to improve the quality of identification in the electric induction motor based on the application of artificial neural networks; has been further developed information model DSSC; An improved method for automated parametric identification of induction motor in the power supply without first creating a reference sample. The results of the research, new methods, approaches and algorithms that allow you to identify and carry out ongoing monitoring of asynchronous motors in the power supply, increasing the probability of detection of emergency operation of the equipment.