Technical Diagnostics and Non-Destructive Testing, 2024, №02

2024 №02 (06)

DOI of Article 10.37434/tdnk2024.02.01

2024 №02 (02)

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"Tekhnichna Diahnostyka ta Neruinivnyi Kontrol" (Technical Diagnostics and Non-Destructive Testing) #2, 2024, pp. 3-10

Investigation of the correlation structure of the vibration signal of the decanter bearing assembly

I.M. Javorskyj^1,2, R.M. Yuzefovych^1,3, O.V. Lychak¹, B.R. Komarnytskyi¹, R.I. Khmil³, O.Y. Smirnova³

¹1G.V. Karpenko Physico-Mechanical Institute of NASU. 5 Naukova Str., 79060, Lviv, Ukraine. Е-mail: roman.yuzefovych@gmail.com
²Bydgoszcz University of Sciences and Technology. 7, Prof. S. Kaliskiego Al., 85796, Bydgoszcz, Poland.
³Lviv Polytechnic National University.12 S. Bandery Str., 79000, Lviv, Ukraine.

The correlation structure of the vibration signal of the decanter bearing assembly was analyzed using the theory and methods of statistics of periodically non-stationary random processes. Indicators for detecting and evaluating the propagation of the defects have been developed. The relationship between the width of the fi ltering bandwidth and the parameters of the amplitude spectrum of the signal variation was investigated. 21 Ref., 3 Tabl., 10 Fig.
Keywords: decanter, vibration, trial period, correlation function, spectral density, band fi ltering, defect development indicator

Received: 02.05.2024
Received in revised form: 22.05.2024
Accepted: 11.06.2024

References

1. Javorskyj, I. (2013) Mathematical models and analysis of stochastic oscillations. PMI, Lviv [in Ukrainian].
2. Javorskyj, I.M., Yuzefovych, R.M., Lychak, O.V., Slyepko, R.T., Varyvoda, M.Z., Semenov P.O. (2022) Diagnostics of gear pair damage using the methods of bi-periodically correlated random processes. Pt 1. Theoretical aspects of the problem. Tech. Diahnost. ta Neruiviv. Kontrol, 4, 4-11. [in Ukrainian]. https://doi.org/10.37434/tdnk2022.04.01
3. Yuzefovych, R.M., Javorskyj, I.M., Lychak, O.V. et al. (2023) Diagnostics of gear pair damage using the methods of biperiodically correlated random processes. Part 2. Investigation of vibration signals of the wind power generator gearbox. Tech. Diahnost. ta Neruiviv. Kontrol, 1, 13-21. https://doi.org/10.37434/tdnk2023.01.02
4. Wang, D., Zhao, X., Kou, L.-L. et al. (2019) A simple and fast guideline for generating enhanced/squared envelope spectra from spectral coherence for bearing fault diagnosis. Mech. Syst. Signal Process., 122, 754-768. https://doi.org/10.1016/j.ymssp.2018.12.055
5. Obuchowski, J., Wyłomańska, A., Zimroz, R. (2014) Selection of informative frequency band in local damage detection in rotating machinery. Mech. Syst. Signal Process., 48, 138- 152. https://doi.org/10.1016/j.ymssp.2014.03.011
6. Antoni, J. (2007) Cyclic spectral analysis in practice. Mech. Syst. Signal Process., 21(2), 597-630. https://doi.org/10.1016/j.ymssp.2006.08.007
7. Ho, D., Randall, R.B. (2000) Optimization of bearing diagnostic techniques using simulated and actual bearing fault signals. Mech. Syst. Signal Process., 14, 763-788. https://doi.org/10.1006/mssp.2000.1304
8. Antoni, J., Borghesani, P. (2019) A statistical methodology for the design of condition indicators. Mech. Syst. Signal Process., 114, 290-327. https://doi.org/10.1016/j.ymssp.2018.05.012
9. Hurd, H.L., Miamee, A. (2007) Periodically correlated random sequences: Spectral theory and practice. Wiley, New York. https://doi.org/10.1002/9780470182833
10. Antoni, J. (2009) Cyclostationarity by examples. Mech. Syst. Signal Process., 23(4), 987-1036. https://doi.org/10.1016/j.ymssp.2008.10.010
11. Napolitano, A. (2020) Cyclostationary processes and time series: Theory, applications, and generalizations. Elsevier, Academic Press.
12. Antoni, J., Borghesani, P. (2019) A statistical methodology for the design of condition indicators. Mech. Syst. Signal Process., 114, 290-327. https://doi.org/10.1016/j.ymssp.2018.05.012
13. Randall, R.B., Antoni, J. (2011) Rolling element bearing diagnostics - A tutorial. Mech. Syst. Signal Process., 25(2), 485-520. https://doi.org/10.1016/j.ymssp.2010.07.017
14. Patel, V.N., Tandon, N., Pandey, R.K. (2012) Defect detection in deep groove ball bearing in presence of external vibration using envelope analysis and Duffing oscillator. Measurement, 45(5), 960-970. https://doi.org/10.1016/j.measurement.2012.01.047
15. Borghesani, P., Pennacchi, P., Ricci, R., Chatterton, S. (2013) Testing second order cyclostationarity in the squared envelope spectrum of non-white vibration signals. Mech. Syst. Signal Process., 40(1), 38-55. https://doi.org/10.1016/j.ymssp.2013.05.012
16. Abboud, D., El Badaoui, M., Smith, W., Randall, B. (2019) Advanced bearing diagnostics: A comparative study of two powerful approaches. Mech. Syst. Signal Process., 114, 604- 627. https://doi.org/10.1016/j.ymssp.2018.05.011
17. Antoni, J., Randall, R.B. (2003) A stochastic model for simulation and diagnostics of rolling element bearings with localized faults. ASME J. Vib. Acoust., 125, 282-289. https://doi.org/10.1115/1.1569940
18. Sawalhi, N., Randall, R.B., Endo, H. (2007) The enhancement of fault detection and diagnosis in rolling element bearings using minimum entropy deconvolution combined with spectral kurtosis. Mech. Syst. Signal Process, 31(6), 2616-2633. https://doi.org/10.1016/j.ymssp.2006.12.002
19. Borghesani, P., Pennacchi, P., Randall, R.B. et al. (2013) Application of cepstrum pre-whitening for the diagnosis of bearing faults under variable speed conditions. Mech. Syst. Signal Process., 36(2), 370-384.1 https://doi.org/10.1016/j.ymssp.2012.11.001
20. Javorskyj, I., Yuzefovych, R., Matsko, I., Zakrzewski, Z. (2022) The least square estimation of the basic frequency for periodically non-stationary random signals. Digit. Signal Process., 122, 103333. https://doi.org/10.1016/j.dsp.2021.103333
21. Javorskyj, I., Yuzefovych, R., Lychak, O., Matsko, I. (2024) Hilbert transform for covariance analysis of periodically nonstationary random signals with high-frequency modulation. ISA Transactions, 144, 452-481. https://doi.org/10.1016/j.isatra.2023.10.025

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