Substantiation of informative amplitudes during registration of acoustic emission signals from the friction zone of tribosystems
In this work, the dependence of the change in the probability density of the distribution of the number of pulses and amplitudes of acoustic emission (AE) signals from the friction zone at the steady-state operation of the tribosystem is obtained. Acoustic vibrations that the tribosystem generates during operation are due to the impact interaction of the roughness of the friction surfaces of their elastoplastic deformation, processes of formation and destruction of frictional links, structural and phase rearrangement of materials, the formation and development of microcracks in the surface layers of contacting bodies, separation of wear particles. The dependence allows you to determine a sufficient number of pulses in the signal frame and their amplitude values for diagnosing tribosystems during their operation. The values of the informative amplitudes of the clusters are experimentally substantiated К2, К3, К4 in relation to the base cluster К1. It is shown that an increase in the informative frequency fAE(fix) from 250 to 500 kHz, increases the value of the informative amplitude to 17,6…43,75%. Based on the results obtained, it was concluded that this fact must be taken into account when developing methods, which will increase the accuracy of diagnosing tribosystems.
The autocorrelation coefficient characterizes the closeness of the linear relationship of the current and previous frames of the series for each of the analyzed clusters. By the value of the autocorrelation coefficient, one can judge the presence of a linear relationship between the values of the recorded amplitudes, their reproducibility in terms of recording time in the steady-state operation of the tribosystem.
To confirm the sufficiency of the selected number of pulses in the clusters of the AE signal frame, as well as the reproducibility of the results of the analysis of frames when they shift in time of registration, an expression is obtained for calculating the autocorrelation function, which reflects the relationship between successive levels of the time series. Based on the results of the experimental data, the values of the autocorrelation coefficients were calculated, equal to 0,82…0,92, which indicates the robustness of the chosen diagnostic technique.
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