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The article analyzes the damageability of electric motors at agricultural processing enterprises in Ukraine. Modern microprocessor systems are being introduced in order to automate the process of determining the technical condition of electric motors. Their software implements complex and informative methods for determining the current state of electric motors based on the analysis of the current values of diagnostic parameters. The current values of not all diagnostic parameters of electric motors are known at the time of determining the technical condition. Therefore, their predicted values are applied. The authors propose to evaluate the current technical condition of electric motors by analyzing the value of the coefficient of its residual life. The values of this coefficient vary from 1 p.p. (the engine is fine) to 0 p.p. (the engine is defective.) An example shows the use of software, namely, Anfis editor of the Fuzzy Logic Tool Box application of the Matlab application package, for creating a mathematical model of the residual life coefficient of an electric motor. It is noted that the error in training the model based on 582 considered variants of combinations of diagnostic parameters and the corresponding values of the residual life of the electric motor does not exceed 0.00288 p.p. (0.2%), and for test voters – 4.1%. Taking into account the large number of mutually influential diagnostic parameters of electric motors, in order to simplify the assessment of the current technical condition, we propose to use the integral diagnostic parameter  the coefficient of residual life. At the same time, it is difficult to determine the technical condition of a working electric motor, because some diagnostic parameters can be measured in a disconnected or disassembled electric motor (for example, measuring the insulation resistance of the stator winding with a megaohmmeter or measuring the diameter of the rotor shaft under the bearing in order to identify the cause of vibration). Therefore, determined at the rate of the process, under such conditions, the technical state of the operating electric motor is predictable  fuzzy. To determine it, one should use the methods and means of neuro-fuzzy modeling. Therefore, the problem of improving the quality of operation of electric motors in agricultural production by improving the quality of their diagnostics is relevant and of great national economic importance.

One of the causes of unwanted interruption in power transformers is its magnetizing inrush current. Due toits current conditions, this current causes the differential relay to misdiagnosis the internal fault of the transformer and leads to an incorrect cut-off command. In this paper, fuzzy systems are using to improve the differential protection of the transformer and to stabilize it against magnetizing inrush current. The basis of the proposed algorithm is that if the cut-off command is sending by the differential relay, by applying Clarke transform to the differential current and using fuzzy logic, the decision to send the cut-off command to the protection relays is made. The proposed algorithm is applying to a sample of the substation transformers model in Iran. The network is simulating in PSCAD/EMTDC software and the output of the simulation is transferring to MATLAB software to apply the proposed algorithm. The simulation results show the efficiency of the proposed algorithm in improving the differential relay.

In 10 kV electrical distribution networks, many power transformers have been in operation for more than 25 years, which exceeds their passport life and in conditions of rapid growth of power generated by photovoltaic stations can cause a decrease in the reliability of these networks. Therefore, it is necessary to improve the quality of modern means of determining the technical condition of such transformers. It is proposed to determine the defective node of the transformer by comparing the current frequency response of the studied transformer with the sample, which is obtained by averaging the values of the frequency characteristics of other transformers, the same type with the test.