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Quarterly magazine OSTU agencies. Registration certificates ПИ № ФС77-36469 on June 3, 2009, ПИ № ФС77-49218 on March 30, 2012, ПИ № ФС77-66605 on July 21, 2016, ПИ № ФС77-71514 on November 1, 2017 and ПИ № ФС77-75780 on May 23, 2019 ISSN: 2220-4245. Subscription index in the official catalog "Subscription publications" of JSC "Russian Post": PP914.
The journal is included in the Russian Science Citation Index and in the List of Russian Scientific Journals .

Search results

  • V.1(45), 2021

    Development of a predictive analysis methodology regarding brush life for rolling stock traction motors according to operating conditions

    At this time, an urgent area of development in the field of railway transport is the reduction of operating costs for maintenance and repair of collector traction motors . The analysis of data from the monitoring of new rolling stock shows that one of the elements affecting the reliability during the operation of traction motors is the collector-brush unit. Failures associated with unsatisfactory operation of the collector-brush unit elements reach 30% of the total number for traction motors. At work of traction electric motors there is a continuous process of mechanical, electric and chemical interaction of electric brushes with a collector, leading to deterioration of electric brushes. During the research, the authors proposed a mathematical model to determine the intensity of wear of electric brushes. The paper provides information about developing an approach that allows using the operating data recorded by locomotive on-board parameter monitoring system to determine the service life of traction motor brushes. For elimination of the problem connected with processing of big arrays of parameter values for calculation, in mathematical model of intensity of wear of electric brushes it is offered to divide the received data into intervals with definition of average values and probability of approach for each of them, and also the technique on realization of the offered decision is resulted. The developed approach allows us to eliminate the need for long-term wear tests on traction motors in operation and reduce not only time, but also financial costs. The reliability of the developed method was assessed by comparing the wear values of different types of electric brushes installed on locomotive traction motors in operation with the calculated values.
  • V.4(36), 2018

    Increase of the resource of current collectors by the means of choice rational combinations of the sectional speed of electrical trains and parameters of the current collection system

    Proposed method for choice rational combinations of the sectional speed of an electric rolling stock under the terms of the maximum mileage with preset wear of current collector stripes and the adjustment of the catenary of existing and projected sections of power supply. The principle of operation and functionality of computer software "Program for the simulation of contact force using a nonlinear autoregressive neural network with exogenous inputs" is considered.
  • V.1(29), 2017

    The algorithm of forecasting of resource of electric brushes traction motors

    In this article the generalized results of researches of change of intensity of wear of electrical brushes in the traction motors of electric locomotives. On the basis of the conducted research the author proposes an algorithm to predict the operating life of the brushes, given the parameters of the operation. In order to increase the reliability of the calculation has been developed algorithms, which allow additionally taking into account the effect of the collector’s surface.
  • V.1(33), 2018

    Application of neural networks at simulation ofa system of current collection on electric railways

    The article deals with the analysis of methods for obtaining statistically reliable data on contact pressure, which are based on the results of inspection trips and data on the design values of the location of the contact wires in the vertical plane andin the path plan. A method for calculating contact pressing with artificial neural networks is proposed. The methods of obtaining statistically reliable data on the contact pressing of current collectors of electric rolling stock without the need for direct measurement, based on the video image of the current collection process and analysis of external factors (weather, operational) accompanying the interaction are considered.
  • V.4(24), 2015

    Prediction of coefficient of hurst by means of methods of analytical forecasting

    The technique of a prediction of coefficient of Hurst on the basis of various ways of a prediction is offered. For a choice of a method of a prediction errors of underestimation and revaluation are entered. It is shown that if not to consider fluctuation of value of coefficient of Hurst, the demanded parameters of a multiservice network, the allocated resources of a network used for calculation or will be insufficiently for high-quality service of the arriving traffic (that is QoS indicators will worsen), or resources of a network will be inefficiently used.
  • V.3(35), 2018

    Improvement of the method of prognostication the indicators of the current collection system under the increase of motion speeds

    A method for predicting the performance of the current collection with increasing speeds using machine learning is proposed. Methods for obtaining statistically reliable data on the contact pressure of current-carrying electric rolling stock without the need for direct measurement based on design data and analysis of external factors (weather, operational) accompanying the interaction are considered.
  • V.4(44), 2020

    Software inertia compensation for industrial temperature sensors in programmable controllers

    The paper deals with the problem of the presence of thermal inertia in thermoelectric converters of general industrial design, used to measure temperature in most technological installations with an ambient temperature above 200 ° C. The aim of the study is to develop an algorithm for predicting the temperature of the environment with known thermal characteristics of the temperature sensor and to implement the algorithm directly in a general industrial programmable logic controller (PLC). As the main method, the work uses the method of mathematical modeling and description of the object in transfer functions and in the form of differential equations. The work uses a previously developed engineering technique for determining the thermal inertia time of industrial sensors, based on a single disturbance and an assessment of the dynamic characteristics of an object. On the basis of the research and mathematical modeling, algorithms for predicting the temperature of the medium by the parameters of the thermal inertia of the temperature sensor and the rate of change of the thermocouple signal have been developed and implemented. The implementation of the algorithms in the TIA Portal environment based on the Siemens Simatic S7-300 PLC using the PID Control library is proposed.