PUBLISHED PAPERS #11.11
| Farid Huseynov, Huseyngulu Guliyev, Elshan Manafov. Determination of Mechanical Faults in Traction Electric Motors Based on an Intelligent Diagnostic System |
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| Abstract. The article is dedicated to controlling the mechanical parameters of traction electric motors using modern methods and tools. In this research, several informative parameters were selected to accurately assess the technical condition of traction electric motors and identify faults related to mechanical components. The normal and critical values of the chosen parameters were determined, enabling real-time monitoring of the motor's technical condition. Data obtained from the motor in real time through sensors are transmitted to an intelligent diagnostic system for analysis. Based on fuzzy logic theory, the expert system model can accurately predict the likelihood of mechanical faults in the motor under varying operating conditions. The expert system model was developed in the MATLAB computational environment using the Mamdani fuzzy inference algorithm within the Fuzzy Logic Toolbox package. Relying on expert knowledge, various decisions can be made regarding the technical condition of the motor based on its informative parameters. By detecting mechanical faults in the motor using sensor information, a signaling and warning system can be installed for critical values, or decisions can be made to directly protect the motor. This approach helps to proactively prevent destructive defects and failures in traction electric motors caused by mechanical faults. |
| Keywords: Traction motor, Mechanical faults, Fault diagnosis, Fuzzy logic, Expert system |
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| DOI: https://doi.org/10.30546/MaCoSEP2025.1391 |