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EN
This research was devoted to the creation of a protection system for electric motors used in industry and transport, based on modern and traditional sensors. In the course of operation, the malfunctions of electric motors have been investigated and it was found that the accident modes occur mainly due to exceeding the permissible values of the current, voltage and temperature parameters. Modern sensors of current, voltage, and temperature have been compared and the most effective ones were selected for use in electric motors. Based on reasoning from these sensors, a protection system for a low-power electric motor has been developed in the laboratory. In addition, in the Multisim application software package, a simulation of the operation of the protection system at different voltage and current values was performed, and a circuit of the sensor control unit and the power source for powering the protection system was constructed. It has been proposed to apply such a multi-parametric complex protection system for electric motors, especially in transport.
EN
This paper is devoted to the development of an effective system for monitoring the technical condition of the axle boxes of rolling stock. To this end, the possibility of solving problems of fault diagnostics based on the theory of fuzzy sets is considered. This allows one note such difficult-to-formalise factors as experience and intuition of a highly qualified expert specialist. It showed that an expert system-based monitoring approach allows evaluation of the technical condition of the axle boxes, characterised by internal and external operating uncertainty. It also proposed the use of parameters such as vibration and noise for comprehensive monitoring of the technical condition of axle box units together with temperature. Furthermore, the combination of these diagnostic parameters and expert system’s possibility to receive all necessary information about the condition of the most critical components of the axle boxes in real-time and analyse the changes in their operational parameters was explored. The stages of modelling an expert system in the Fuzzy Logic Toolbox package of the MATLAB computing environment are presented.
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