The possibility of using modern contactless methods of diagnostics and control of electrical equipment is considered. One such method is the use of artificial neural networks to assess the current state of electrical equipment, which allow timely detection of various malfunctions, assess its condition and prevent possible failures.
Extralong pipelines are heated by means of induction resistive systems are used, which are a short-circuited coaxial line. When calculating the heat generation power of such a system, it is necessary to take into account the surface effect and the proximity effect in the steel pipe, which lead to a significant increase in its electrical resistance. The total resistance of a steel pipe of an induction-resistive heating system (IRH) was determined by analytically solving a magnetodynamic problem. The verification of the methodology for determining power was carried out using physical and mathematical simulation of the operation of the IRH system at various current loads. For physical simulation, an experimental facility was installed, which is a section of the IRH system. During the tests, the current was recorded and the temperatures of the conductor, cable surface, pipe, and environment were measured. Transient thermal processes implemented at the facility are described by the differential equation of nonstationary thermal conductivity in a one-dimensional axisymmetric formulation. The volumetric power of heat release is determined using the proposed methodology. A comparative analysis of the temperature dependences obtained using physical and numerical experiments indicates a fairly good agreement between the results.
A method for the development of a linear short-stroke motor for the industrial use as a drive mechanism of a diaphragm pump is considered. The features of the proposed motor design are associated with the specific operating conditions under reciprocating motion with a short stroke length. The motor calculation is presented, and the results of a simulation accompanying the process of its development and used in the prototype manufacturing are shown.
An increase in the capacity of cable lines is possible due to the use of mathematical models of heat and mass transfer processes instead of determining the long-term permissible currents using regulatory documents that do not take into account the full load mode of the cable structure. The introduction of digital technologies into the processes of control and management of power-supply systems will ensure an increase in the reliability and quality in these systems. The paper suggests the introduction of a decision support system (DSS) into the system for control over the load modes of cable units, which makes it possible to determine the optimal load modes for specific operation conditions based on the temperature restrictions. The DSS, which is based on mathematical models, helps to develop control actions to force a reduction in the load of some lines when permissible temperatures are possibly exceeded. The recommendations for reducing the load should take into account the range of possible working currents for each line, which depends on the customer category and technological capabilities. The optimal operation mode, for which the insulation temperatures are not higher than permissible values and a relative decrease in the power consumption is minimum, has been selected.
A technique for determining the friction characteristics of pairs of mechatronic systems in the mode of forced steady oscillations is considered. A mechatronic oscillatory system uses a synchronous electric machine with permanent magnets on the rotor and an oscillation mode control system. Determination of the dependence of the friction torque on the angular velocity using the Stribeck curve occurs under conditions close to operational ones, that is, with continuous movement, variable angular velocity, and a change in the direction of movement. Results of experimental studies and simulations using MATLAB/Simulink are presented.
The concept of an intelligent transport system representing a “person–vehicle” integrated system of interaction between transport subjects is considered. Properties of the system that are considered intelligent are presented. In particular, such characteristics such as learning ability, classification ability, and adaptation are discussed. As an example, an automated control system for railway crossings that regulate the flow of vehicles across railway tracks is considered. An algorithm is proposed based on the principle of intelligent control using machine learning and self-tuning under the action of destabilizing factors. A unit diagram of an intelligent control system for crossing protection devices is also presented.
This article discusses simulation of a circular interpolator developed according to the principle of differential analyzers on the basis of two coordinate electric servo drives with a stepper electric motor using the MATLAB/Simulink software during processing of the technological radius of workpiece. A simulation model has been obtained, including a model of a circular interpolator and models of two servo electric drives based on a stepper motor, which move, for example, along the X and Y coordinates of various coordinate machines with numerical control, using a stepper motor. The contour errors of servo electric drives when processing the radius of a circle were obtained, as well as graphs of transient processes of servo electric drives for various interpolation parameters. The resulting tracking errors are not only necessary for diagnosing the inertial properties of the electric drive, but also can be considered as a consequence of adjusting the control system as a whole.
The results of a study of the noise immunity of a receiver of a continuous automatic locomotive signaling channel under the influence of sinusoidal interference from power lines are presented. It is shown that the use of a block with an insensitivity zone in the receiver makes it possible to effectively combat sinusoidal interference from power lines in the automatic locomotive signaling channel. As a result of the use of such a block, the interference interval from the power line was reduced from 11.7 to 4.5 s.
The problem of interference suppression in the signals of an automatic locomotive signaling system is considered as a problem of separating the signals of a locomotive signaling system and interference in an additive mixture of these signals. To solve this problem, it is proposed to use statistical algorithms for signal separation based on a priori information concerning the properties of signal sources. Studies on the potentialities of statistical interference suppression algorithms have been carried out based on computational experiments with the use of reference signals. Based on the results of computational experiments, a comparative analysis of the efficiency of statistical algorithms under the conditions of different interference types affecting the rail channel is presented. The computational experiments have shown that the use of statistical algorithms makes it possible to suppress interference, the level of which is comparable to the level of signals inherent in the locomotive signaling system.
The architecture of interaction of modules of an automated monitoring and diagnostic system with wayside devices of railway automation and telemechanics is presented. An example of the operation of monitoring system of a rail line condition is considered. Various functions of an automated monitoring and diagnostic system are presented, including monitoring the condition and serviceability of wayside devices, monitoring the resistance of insulating and conductive joints, predicting possible failures, and determining the specific location of their occurrence. The principle of using artificial neural networks for diagnosis and monitoring system is outlined, various neural network training models are considered, and the most appropriate learning model is identified.
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