APPLICATION OF A FUZZY LOGIC SYSTEM TO DETERMINE THE RESOURCE OF AN ASYNCHRONOUS MOTOR
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Keywords:
asynchronous motor, modeling, fuzzy logic, isolation, residual resource, diagnostics.Abstract
The article analyzes the method for determining the resource of an asynchronous motor through the use of fuzzy logic, explains the structure of the developed Fuzzy Logic System and the results of experiments on determining the resource of an asynchronous motor. The problems that are necessary to solve unambiguously determine the remaining resource of an asynchronous motor are formulated. In this paper, the developed fuzzy logic system will allow us to reasonably determine the residual life of an asynchronous motor based on the results of measuring the no-load current, air gap, insulation resistance, power factor, winding resistance at direct current, stator winding insulation absorption coefficient, stator winding insulation polarization coefficient, insulation modulus, stator temperature and bearing condition assessment. The results obtained during their implementation will help prevent failure of the asynchronous motor and reduce material damage associated with downtime of technological equipment, elimination of the consequences of accidents and repair of the failed electric motor itself. A method for determining the remaining resource of an asynchronous motor is developed using a fuzzy logic system in the Matlab software environment and the FuzzyLogic package. A fuzzy logic system is developed for determining the remaining resource of an asynchronous motor. A detailed study of the results of computer modeling is carried out , which indicate that the fuzzy logic system for determining the remaining resource of an asynchronous motor functions properly and is ready for operation. A fuzzy logic system normalizer is developed for determining the remaining resource of an asynchronous motor. The launch of the file content in the Matlab command line is analyzed in detail, which showed the result of the entire system of non-clear logic at minimum, maximum and average values of control parameters.
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