Vibration diagnostics of gas turbine engines bearing assemblies technical condition with rhythmograms and scatterograms

DOI: 10.34759/vst-2021-4-151-162

Аuthors

Balakin D. A.^1*, Zubko A. I.^2**, Zubko A. A.^3***, Shtykov V. V.^1****

1. National Research University “Moscow Power Engineering Institute”, 14, Krasnokazarmennaya str., Moscow, 111250 Russia
2. Lyulka Experimental Design Bureau, branch of the United Engine Corporation – Ufa Engine Industrial Association, 13, Kasatkina str., Moscow, 129301, Russia
3. Moscow Aviation Institute (National Research University), 4, Volokolamskoe shosse, Moscow, А-80, GSP-3, 125993, Russia

*e-mail: dabalakin@yandex.ru
**e-mail: zbk2@yandex.ru
***e-mail: zbk.anna@mail.ru
****e-mail: shtykovvv@ya.ru

Abstract

The introduction to the article is focused on the problem of early diagnostics of the aircraft gas turbine engine bearings. Particularly, the gas turbine engine bearing functioning period disrupts namely at its early developmental stage, which does not always succumbs to estimation by the conventional methods. The authors suggest employing the apparatus widely known in medicine practice to analyze the occurring quasi-periodicity, namely rithmogram and scatterogram.

A rithmogram plotting is being realized based on the developed technique. The technique in its turn bases on the correlation processing principles, wavelet transform theory and Hermite transform. Briefly, the gist of the technique consists of the following: mutual correlation function of the studied signal of the bearing and reference function is being computed. The reference function is being plotted based on Hermite transform, and represents mirror reflection of the impulse characteristic of the complex quasi-matched filter. Wavelet processing principles application (scaling parameter variation) allows refining positions of the correlation function peaks. After the cross-correlation function threshold processing we obtain rhythmogram and scatterogram of the signal under study.

Further, the article considers processing of real signals of gas turbine bearing. Spectral and statistical analysis of the obtained rhythmograms and scatterograms is being performed. Inferences are being drawn on the state of the bearings under study.

Conclusion considers further prospects of the rhythmograms and scatterograms application as diagnostics tools for aircraft gas turbine engines.

Keywords:

vibration diagnostics of rotor bearings, Hermite transformation, rhythmogram, scatterogram, quasi-periodicity

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