Development of the system for vibration diagnosis of bearing assemblies using an analog interface

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.144533

Keywords:

vibration diagnosis, gas turbine engine, differential charge amplifier, bearing assembly, tracking notch filter

Abstract

We have proposed a system for early vibration diagnosis of gas-pumping units, specifically bearing assemblies with improved metrological characteristics. The technique makes it possible to solve the task of early diagnosis of roller bearings under adverse conditions of application. The study has shown that this is achieved through the use of tracking notch filters based on N-channel structures using the iterative-integrating converters. The simulation results of the 4-channel filter under actual input signals of bearing damage have demonstrated its effectiveness. Based on this, we have built the resulting model for the filter’s output signal. Here we show a functional circuit for the root-mean-square values detector with a model of the output signal from the tracking notch filter at actual input signals. To build a model of signal at the input to a root-mean-square values detector, we determined filter responses for each frequency, which is responsible for a certain damage. The time of analysis was selected so that it was equal to a period of the minimum beat frequency, that is, Ta=164 ms (for a bearing of type 222).

We investigated effectiveness of the device by simulating a damage to an actual gas turbine engine’s bearing. The procedure for analysis has been proposed and the generalized vibro-diagnostic criterion has been suggested, which takes into consideration the degree of engine’s load. This improves accuracy and reliability of preliminary analysis when diagnosing a roller bearing at the stage of the origin of the damage.

Characteristics are given for the electrometric measuring amplifier for work with piezoelectric sensors and the proposed charge measuring amplifier to work with piezoelectric sensors. Under condition for the imbalance of the input link, which is due to the non-identity of parasitic capacitances of the input cable. It is shown that the penetration of a network disturbance to the output of the charge measuring amplifier provides for the signal/noise ratio that is two orders of magnitude better than that for the electrometric measuring amplifier.

Author Biographies

Vasyl Dovhan, SE «UKRMETRTESTANDART» Metrologichna str., 4, Kyiv, Ukraine, 03143

Deputy Head

Scientific and Research Department of Measurements of Electrical and Magnetic quantities measurements

Vladimir Kvasnikov, National Aviation University Kosmonavta Komarova ave., 1, Kyiv, Ukraine, 03058

Doctor of Technical Sciences, Professor, Head of Department

Department of Computerized Electrical Systems and Technologies

Dmitro Ornatskiy, National Aviation University Kosmonavta Komarova ave., 1, Kyiv, Ukraine, 03058

Doctor of Technical Sciences, Associate Professor, Head of Department

Department of Information and Measuring Systems

References

  1. Smirnov, V. A. Vibracionnaya diagnostiki podshipnikov kacheniya dvigatelya NK-12ST gazoperekachivayushchego agregata GPA-C-6,3. Available at: http://www.vibration.ru/12nks/12nks.shtml
  2. Ravliuk, V. H. (2010). Vibrodiahnostyka ta metody diahnostuvannia pidshypnykiv kochennia buksovykh vuzliv vahoniv. Sbornik nauchnyh trudov Doneckogo instituta zheleznodorozhnogo transporta, 21, 177–189.
  3. Monitorizaciya mekhanicheskih kolebaniy mashinnogo oborudovaniya (1987). Perevod tekhnicheskogo obzora No. 1. Nerum.
  4. Frariry, J. L. (2002). Pitfalls in the Analysis of Machinery Vibration measuremеnt. Sound and Vibration, 18–24.
  5. Bilosova, A., Bilos, Ya. (2012). Vibracionnaya diagnostika. Ostrava, 113.
  6. Azovtsev, A. Y., Barkov, A. V., Carter, D. L. Improving the accuracy of rolling element bearing condition assessment. Available at: http://www.vibrotek.com/articles/abcvi96/abcvi96.htm
  7. Rutkovskiy, V. Yu., Suhanov, V. M., Glumov, V. M. (2007). Sistema izmereniya parametrov radial'nyh vibraciy vala gazoturbinnoy ustanovki. Datchiki i sistemy, 8, 2–7.
  8. Patyukov, V. G. (2003). Fil'traciya signalov chastotnyh datchikov. Datchiki i Sistemy, 5, 2–4.
  9. Herris, F. Dzh. (1978). Ispol'zovanie okon pri garmonicheskom analize metodom diskretnogo preobrazovaniya Fur'e. TIIER, 1, 60–67.
  10. Marchenko, B. G., Myslovich, M. V. (1992). Vibrodiagnostika podshipnikovih uzlov elektricheskih mashin. Kyiv: «Naukova dumka», 196.
  11. Babak, S. V., Myslovich, M. V., Sysak, R. M. (2015). Statisticheskaya diagnostika elektrotekhnicheskogo oborudovaniya. Kyiv, 456.
  12. Chen, A., Kurfess, T. R. (2018). A new model for rolling element bearing defect size estimation. Measurement, 114, 144–149. doi: https://doi.org/10.1016/j.measurement.2017.09.018
  13. Ying, Y., Li, J., Chen, Z., Guo, J. (2018). Study on rolling bearing on-line reliability analysis based on vibration information processing. Computers & Electrical Engineering, 69, 842–851. doi: https://doi.org/10.1016/j.compeleceng.2017.11.029
  14. Schmidt, S., Heyns, P. S., Gryllias, K. C. (2019). A discrepancy analysis methodology for rolling element bearing diagnostics under variable speed conditions. Mechanical Systems and Signal Processing, 116, 40–61. doi: https://doi.org/10.1016/j.ymssp.2018.06.026
  15. Klein, R., Masad, E., Rudyk, E., Winkler, I. (2014). Bearing diagnostics using image processing methods. Mechanical Systems and Signal Processing, 45 (1), 105–113. doi: https://doi.org/10.1016/j.ymssp.2013.10.009
  16. Smith, W. A., Randall, R. B. (2015). Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study. Mechanical Systems and Signal Processing, 64-65, 100–131. doi: https://doi.org/10.1016/j.ymssp.2015.04.021
  17. Seimert, M., Gühmann, C. (2017). Vibration based diagnostic of cracks in hybrid ball bearings. Measurement, 108, 201–206. doi: https://doi.org/10.1016/j.measurement.2017.03.001
  18. Smith, W. A., Fan, Z., Peng, Z., Li, H., Randall, R. B. (2016). Optimised Spectral Kurtosis for bearing diagnostics under electromagnetic interference. Mechanical Systems and Signal Processing, 75, 371–394. doi: https://doi.org/10.1016/j.ymssp.2015.12.034
  19. Chen, B., Shen, B., Chen, F., Tian, H., Xiao, W., Zhang, F., Zhao, C. (2019). Fault diagnosis method based on integration of RSSD and wavelet transform to rolling bearing. Measurement, 131, 400–411. doi: https://doi.org/10.1016/j.measurement.2018.07.043
  20. Dovhan, V. V., Ornatskyi, D. P. (2010). Pat. No. 60405 UA. Prystriyi dlia vibrodiahnostyky pidshypnykovykh vuzliv. MPK: G01M 13/04. No. u201008439; declareted: 06.07.2010; published: 25.06.2011, Bul. No. 12.
  21. Karasev, V. A. Maksimov, V. P., Sidorenko, M. K. (1978). Vibracionnaya diagnostika gazoturbinnyh dvigateley. Moscow: Mashinostroenie, 132.
  22. Babak, V. P., Babak, S. V., Eremenko, V. S., Kuc, Yu. V., Marchenko, N. B., Mokiychuk, V. M. et. al.; Babak, V. P. (Ed.) (2014). Teoreticheskie osnovy informacionno izmeritel'nyh sistem. Kyiv, 832.
  23. Makarenko, V., Chermyanin, A. (1999). Maloshumyashchiy usilitel' dlya p'ezokeramicheskih datchikov. Elektronnye komponenty i sistemi, 5 (21).
  24. Barns, Dzh. (1990). Elektronnoe konstruirovanie: Metody bor'by s pomekhami. Moscow: Mir, 238.
  25. Ornatskyi, D., Dovhan, V. (2018). Doslidzhennia parametriv N-kanalnykh filtriv dlia vibratsiynoho analizu pidshypnykovykh chastot. Metrolohiya ta prylady, 1, 46–52.

Downloads

Published

2018-10-16

How to Cite

Dovhan, V., Kvasnikov, V., & Ornatskiy, D. (2018). Development of the system for vibration diagnosis of bearing assemblies using an analog interface. Eastern-European Journal of Enterprise Technologies, 5(9 (95), 51–59. https://doi.org/10.15587/1729-4061.2018.144533

Issue

Section

Information and controlling system