In systems for monitoring, diagnostics and recognition of the state of various types of objects, an important aspect is the reduction of the volume of measured signal data for its transmission or accumulation in information bases with the ability to restore it without significant distortion. A special type of signals in this case are packet signals, which represent sets of harmonics with multiple frequencies and are truly periodic with a clearly distinguishable period. Signals of this type are typical for mechanical, electromechanical systems with rotating elements: reducers, gearboxes, electric motors, internal combustion engines, etc. The article considers a number of models for reducing these signals and cases of priority application of each of them. In particular, the following are highlighted: the discrete Fourier transform model with a modified formula for restoring a continuous signal, the proposed model based on decomposition by bordering functions and the discrete cosine transform model. The first two models ideally provide absolute accuracy of signal restoration after reduction, the last one refers to reduction models with information loss. The main criteria for evaluating the models are: computational complexity of the implemented transformations, the degree of implemented signal reduction, and the error in restoring the signal from the reduced data. It was found that in the case of application to packet signals, each of the listed models can be used, the choice being determined by the priority indicators of the reduction assessment. The application of the considered reduction models is possible in information and measuring systems for monitoring the state, diagnostics, and control of the above-mentioned objects.

Keywords: reduction model, measured packet signal, discrete cosine transform, decomposition into bordering functions, reduction quality assessment, information-measuring system

The construction of a regression model of errors in the approximation of the current curve from factors affecting this error is described. The following factors are selected as influencing factors: the number of coefficients of the Bessel-Fourier decomposition and the number of points on which the original function is constructed. Experimental data were obtained as a result of modeling electrical processes occurring in a pulsed magnetization reversal system.

Keywords: permanent magnet, regression model, Bessel-Fourier decomposition, approximation, momentum, factors, function, curve, momentum, error

When creating a model of a nonlinear electrical system based on differential equations, it is important to keep in mind that ordinary differentiation does not give an adequate mathematical idea of ​​the nonlinear physical processes taking place. Even in the simplest case of a conductor with a current, the construction of an adequate model is only possible if the tensor approach is applied. From this point of view, any electrical system is an object of tensor methodology. A typical example of a non-linear electrical system is an AC electromagnetic drive. The nonlinear nature of the processes in such devices is due to a number of reasons. The main reasons are: current displacement in the winding of the AC electromagnetic drive and saturation of the steel of the magnetic circuit in the process of magnetization. Both phenomena admit tensor description, which is confirmed by the research presented in the article.

Keywords: dynamic characteristic of magnetization, electromagnet, mathematical model, tensor methodology

it is known that the human body consists of water, proteins, minerals and adipose tissue, the sum of which is body weight. An important condition for maintaining health is the balance of the main components found in the internal organs of a person. Currently, the development of modern technologies allows you to find out the exact composition of your body, as well as internal organs, without complicated analyzes, using special devices that are based on measuring the bioimpedance of living tissue. Absolutely all tissues can conduct electric current, while the more water in the tissues, the more electrical conductivity and less resistance., The opposite is also true. Bioimpedance analysis measures the reactance of parts of the human body at different frequencies. On the basis of which the characteristics of the composition of the body or internal organs are calculated. Meanwhile, the measurement of the impedance of a person or his internal organs is associated with certain problems. So distorting factors can be the position of a person in space, improperly prepared areas of the body from which data are taken, improper placement of electrodes, poor contact. The aim of this work was to construct a regression model of a device for measuring the impedance of a biological object (BO), reflecting the contribution of the BO impedance to the total impedance of the entire measurement section.

Keywords: distributed information processing system, self-similar flow, average response time of the system, simulation, object-oriented concept, agent-based and discrete-event modeling