Diagnosis of traction electric motors of modern rolling staff using artificial intelligence

The article is devoted to topical issues of control and diagnostics of asynchronous traction motors of locomotives using artificial networks. The article presents a mathematical model of a neural network and the structure of the organization of control of the technical state of ATED and also substantiates the expediency of proactive diagnostics, which allows identifying defects in advance at the earliest stage of their development. The mathematical model given in the article expresses all the physical processes that take place in a rotor of ATED by specific mathematical expressions and equations. Graphs and plots presented in the article show apparent changes that happen in rotor or rod malfunction cases and the current spectral graph in ATED in full load case. All the results are obtained using the MATLAB / Simulink software environment, which allows analysis and investigation of asymmetric modes of variable states of an asynchronous traction motor of locomotives.

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