IDENTIFICATION OF THE COEFFICIENTS OF WAVELET ANALYSIS FORMED ON THE BASIS OF THE KERNEL OF THE INTEGRAL MODULATION
Vibration analysis is essential for the improvement of condition monitoring and fault diagnosis of rotating machinery. Many signal analysis methods might extract useful information from vibration data. Currently, most of these methods use spectral analysis based on the Fourier transform (FT). However, these methods have some limitations; this applies to non-stationary signals. The paper defines the possibility of using the nuclei of the operator of the integral modulation as a function of the wavelet transform and proposes an algorithm for the identification of the wavelet analysis coefficients for the cases of non-stationary input sequence and non - simulated internal dynamics of the internal combustion engine. The continuous wavelet transform has the ability to construct a frequency-time representation of the signal, which offers a very good localization of time and frequency. Time-frequency analysis is a new method of signal processing that allows you to view time and frequency information at the same time. It shows combined results from time and frequency analysis in a three-dimensional way that plots amplitudes against time and frequency axes. For applications analysis of engine vibration method for time-frequency is very useful in that most cases referred by the vibration of the engine as the activities of the combustion and valve have fixed the occurring time of the specific crank mechanism. When you perform a time-frequency analysis of these events, you can determine the time of occurrence and the frequency of the locations. Many methods of research devoted to the problem of recognition of the technical state, and the diagnosis of mechanisms by vibration parameters using traditional methods, consider the analysis of the spectrum of the vibration signal of the internal combustion engines, which allows to identify the frequency composition of the processed signal. However, this method is not informative enough because of the large range of existing ice, the mechanisms of which differ in design and weight, which leads to the complexity of determining defects due to different frequency portraits of the studied signals. The scheme of formation of the wavelet transform coefficients using the wavelet functions of the integral modulation operator as the nucleus is presented. The study was conducted in Matlab/Simulink environment.