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The article presents the results of modeling the force fields in the elements of the wheel-motor unit of the electric locomotive 2ES10. The mathematical model is obtained on the basis of the Lagrange equations of the ΙΙ kind. A design scheme for the study of the dynamic behavior of the wheel-motor unit is presented. Expressions for the deflection of the elastic elements of the traction motor suspension, elastic and dissipative forces are given. A method for determining the vector force field at the articulation site of the bracket and thrust suspension TEM is proposed.

The article describes three variants of the mathematical model of the sensitivity function of the magnetoinduction sensor for assessing the influence of various sensor parameters in the electromechanical system «wheel - rail - magnetoinduction sensor» for diagnosing the technical condition of the rolling surface of the rolling wheels of rolling stock in the process of its movement over the sensor. An example of an algorithm for identifying defects located on the surface of the wheel rolling circle is described. The proposed multi-vector mathematical model allows simulating various defects on the rolling surface of the wheel, developing and testing new algorithms for processing the output signal of the sensor on the basis of modern hardware and software. The implemented defect identification algorithm is based on the property of the centrally symmetric form of the sensitivity function of the magnetoinduction sensor and the allocation of a useful signal corresponding to a certain type of defect, based on the application of a mutual correlation function and the assessment of its maximum and minimum values in comparison with the specified thresholds and confidence intervals. The main requirement for the implementation of the model is the uniform movement of the train above the sensor along a straight section of the rail track. This article discusses only one of the possible digital signal processing algorithms, but the proposed model allows us to compare the efficiency of other possible algorithms identification of defects in the rolling surface of wheelsets. The developed model confirms the prospects of using magnetic induction sensors for identification of not only visible, but also hidden defects on the rolling surface of the wheel in the process of movement of the train.