The paper analyzes the prospects for the formation and implementation of digital data transmission technologies on railways of Kazakhstan, taking into account the potential for the development of high-speed railway transport (HSRWT), as well as new approaches for solving the development problems of advanced automated dispatch control systems (ADCS). It was shown that the solution of these problems is possible by automatization of the train traffic coordination based on the use of the potential of the GPRS data transmission technology. The work further developed models and algorithms used in ADCS of the railway transport. There has been carried out the formalization of the tasks of navigation data transmission for ADCS and for the subsystems of the railway rolling stock movement coordination, including HSRWT using GPRS data transmission technology. Also, the article describes a modernized algorithm for simulation of the GPRS channels operation in ADCS. The proposed algorithm differs from the existing ones by the ability to make predictive estimates for determination of the railway rolling stock location. Also, the developed algorithm provides opportunities for coordination of the trains movement, taking into account the optimization of the GPRS resources use.
Automation of data processing of contactless diagnostics (detection) of the technical condition of the majority of nodes and aggregates of railway transport (RWT) minimizes the damage from failures of these systems in operating modes. This becomes possible due to the rapid detection of serious defects at the stage of their origin. Basically, in practice, the control of the technical condition of the nodes and aggregates of the RWT is carried out during scheduled repairs. It is not always possible to identify incipient defects. Consequently, it is not always possible to warn personnel (machinists, repairmen, etc.) of significant damage to the RWT systems until their complete failure. The difficulties of obtaining diagnostic information is that there is interdependence between the main nodes of the RWT. This means that if physical damage occurs at any of the RWT nodes, in other nodes there can also occur malfunctions.
As the main way to improve the efficiency of state detection of the nodes and aggregates of RWT, we see the direction of giving the adaptability property for an automated data processing system from various contactless diagnostic information removal systems. The global purpose can be achieved, in particular, through the use of machine learning methods and failure recognition (recognition objects). In order to improve the operational reliability and service life of the main nodes and aggregates of RWT, there are proposed an appropriate model and algorithm of machine learning of the operator control system of nodes and aggregates. It is proposed to use the Shannon normalized entropy measure and the Kullback-Leibler distance information criterion as a criterion of the learning effectiveness of the automated detection system and operator node state control of RWT. The article describes the application of the proposed method on the example of an automatic detection system (ADS) of the state of a traction motor of an electric locomotive. There are given the test data of the model and algorithm in the MATLAB environment.
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