Volodymyr Isaenko’s research while affiliated with National Aviation University and other places

The article describes the approach to the formation of a simulation model of information signals, which are typical for objects with different types of defects. The dispersive analysis of the signal spectrum components in the bases of the discrete Hartley transform and the discrete cosine transform is carried out. The analysis of the form of the reconstructed information signal is carried out depending on the number of coefficients of the spectral alignment in Hartley bases and cosine functions. The basis of orthogonal functions of a discrete argument is obtained, which can be used for the spectral transformation of information signals of a flaw detector. A function was obtained approximating the distribution of the values of each of the coefficients of the spectral decomposition depending on the degree of damage (defectiveness) of the sample under study. It proved the need to use splines in the approximation of equations. The advantage of the splines is obtaining reliable results even for small degrees of interpolation equations, moreover, the Runge phenomenon does not arise, which occurs when using high-order polynomial interpolation.

The article analyzes the current state of methods and means of monitoring air pollution in Ukraine. The issues of the formation of pollutants during the combustion of various types of fuel (gaseous, liquid, solid) in large power plants are considered. The data about the largest sources of air pollution in Ukraine are given. The main disadvantages of the model of the spread of pollutants in the air, which is used as a base, are reflected. The current state of air pollution monitoring systems, both in Ukraine and in other countries, is investigated. The improvement of the existing air pollution monitoring system based on unmanned aerial vehicles is proposed.

It is proposed to apply the wavelet transform to localize in time the frequency components of the information signals in this article. The wavelet transform allows to fulfil time-frequency analysis of signals, which is very important for studying the structure of a composite material from the mode composition of free oscillations. The proposed approach to the development of information signals using wavelet transform makes it possible to further study the nature of the occurrence of free oscillations and the propagation of acoustic waves in individual layers of composites and to study the change in the structure of composites from the changes in the three-dimensional wavelet spectrum. 1 Introduction Information signals obtained in the process of diagnosing composite materials by low-frequency acoustic methods belong to the class of single-pulse signals with locally concentrated features. These are, for example, signals of free oscillations, whose modes have not only frequency, but also temporal distribution, signals of impulse impedance method change frequency and current carrier phase for one radio pulse, signals of low-speed impact method locally change their shape depending on material defectiveness. For such signals, the task of identifying diagnostic signs is significantly more difficult than for signals in which the information component is evenly distributed over the observation interval [1, 2]. This is explained by the fact that diagnostic signs are focused on small time intervals or fragments of signal realization, and the signal itself has a rather complex form that cannot be described by a formal constructive model. The most common methods for isolating diagnostic features of such signals are [3, 4, 5, 6]:  methods for evaluating the integral characteristics-the center of mass of the pulse, the similarity coefficients, etc. These methods have high noise immunity, but have very little sensitivity to local changes in signal parameters;