Search results

Modern locomotive on board microprocessor-based control systems (MSU) can be used for not only controlling locomotive equipment, but for analyzing the process of their functioning too by means of mathematical statistics. It is confirmed by authors of this article. Through the article is offered method of nearby-failure condition diagnostic by the means of MSU data correlation analysis.

In article the question about possibility of extension of service life of carriage wheels by influence on technological parameters of restoration of their driving profile is considered. The correlation analysis of statistical data on volumes of machining and the size of defects on a driving surface of the wheels coming to repair is made. The mechanism of purpose of an allowance for machining of a driving profile of a wheel which will allow to reduce an unreasonable consumption of metal of a rim of a wheel in shaving is offered.

The article considers the current situation regarding the organization of control over the use of traction and energy resources of JSC «Russian Railways». The main provisions of the proposed method are stated. The influence factors on the specific electric power consumption of electric locomotives of series 2ES6 and VL10, as well as the evaluation of the quality of the constructed models of multiple nonlinear regression were estimated. New scientifically grounded technological solutions and developments are proposed that allow to reduce the specific consumption and unproductive losses of electric energy within the boundaries of the railway accounting areas.

The article analyzes the results of the assessment operating time and power consumption of compressor equipment service locomotive depo Moscow West-Siberian Railway. The algorithms for data preparation for modeling and evaluating the efficiency of the production process are presented. The main factors influencing the power consumption of the compressor equipment are determined and the results of the assessment of their influence are presented. On the basis of the dependences obtained, a mathematical model of the process of power consumption of compressor equipment using fuzzy neural networks and its accuracy is determined. The interface of the developed program complex is presented at an estimation of influence of factors on process of power consumption of the equipment service locomotive depo Moscow West-Siberian Railway.