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The paper is vibration investigation in a case of guiding of railroad vehicle in curves with low radius. Experimental methods. Examine results of the investigation of vibrations on box bearing of railroad locomotive in a case of mountain trucking with large count of curves with low radius. It is show, that in a case of locomotive guiding in a low radius curves a pseudo-random vibration arise. The level of the pseudo-random vibration in a low radius curves exceeds the vibration in the rail joint, but vibration in the guiding is semi continuous. In a case of locomotive working, also the harmonics of gearing is shown. The spectral density of vibration accelerations is presented in a three-dimensional form, coded in color on a two-dimensional time-frequency diagram for estimating the vibration spectra and their probable sources.

The expediency of introducing dynamic models of defect development into the practice of vibration diagnostics of rotor mechanical units is substantiated. It is shown that as a basis for the creation of models it is advisable to use empirical data. An example of a dynamic model of a small gear defect of a wheel-gear unit is given. The approximate amount of work on the creation of dynamic models is determined. Methods of realization of dynamic models of defects "in the big" are offered.

The article presents a criterion for choosing the optimal type of wavelet function for digital processing of current and voltage values in the analysis of the electric network mode. The increase in the share of electric receivers that distort the quality of electricity sets the task for researchers to use more advanced mathematical tools for analyzing and modeling such power supply systems. The discrete wavelet transform allows the harmonic analysis of currents and voltages under non-stationary non-sinusoidal modes. One of the key tasks in the development of digital technologies in the electric power industry is the creation and development of intelligent electric networks with the introduction of new algorithms for digital data processing and decision making. In this case, algorithms for compression and remote recovery of data on the consumption and production of electrical energy in the cloud should be developed. The wavelet transform eliminates the negative spreading effect characteristic of the Fourier transform in the analysis of non-sinusoidal non-stationary modes. Based on the Parseval equality, the wavelet transform makes it possible to determine the spectrum energy of individual frequency ranges determined by the depth of decomposition and the sampling frequency of the signal under study. The calculation of the energy of the spectrum of wavelet coefficients allows the compression of the flow volume of instantaneous values of voltages and currents. The article presents the results of continuous and discrete wavelet current conversion when switching a battery of static capacitors. Information compression ratio exceeded 5.3. The wavelet transform was performed using eight different wavelet functions. The criterion for choosing the optimal mother wavelet determines the condition of the maximum energy of the spectrum and the minimum standard deviation when restoring the original signal.

Recently, for the analysis of complex nonlinear processes, more and more attention is paid to the mathematical apparatus of wavelet transform. This is due to the fact that unlike the traditional Fourier transform, the wavelet transform provides information about the signal under study in the time-frequency domain. The purpose of research is to analyze and simulate a non-sinusoidal non-stationary mode based on the packet wavelet transform, the use of this method for transmitting the digital data stream of the signal under study. The simulation was carried out using the software package Simulink. In the study found that packet wavelet transform with high precision allows to determine the presence of higher harmonics in the power system, the efficiency of using wavelet transform to compress digital data stream of the test signal.