Methodology for monitoring the technical condition of GPU type GTK-25i in the process of operation

Authors

  • L. M. Zamikhovskyi Ivano-Frankivsk National Technical University of Oil and Gas, 15 Karpatska Street Ivano-Frankivsk Ukraine, 76019
  • O. L. Zamikhovska Ivano-Frankivsk National Technical University of Oil and Gas, 15 Karpatska Street Ivano-Frankivsk Ukraine, 76019
  • V. V. Pavlyk Ivano-Frankivsk National Technical University of Oil and Gas, 15 Karpatska Street Ivano-Frankivsk Ukraine, 76019

DOI:

https://doi.org/10.31471/1993-9965-2020-2(49)-106-116

Keywords:

technical condition, technique, discriminant analysis, identifier, correlation, diagnostic feature, technological vibroacoustic parameters.

Abstract

  In the early 1980s, 120 gas compressor units (GPU) type GTK-25i were installed on the Urengoy-Pomary-Uzhgorod transcontinental gas pipeline, and three of them are in operation at CS-39 “U-P-U” of the Bogorodchansk Linear Production Department of trunk gas pipelines. Today, about 80% of GPU type  GTK-25i have worked out the established service life, or those close to it. Their further operation does not ensure reliable and efficient operation, and therefore numerous failures and accidents occur, leading to significant economic losses.  Methods of parametric and vibroacoustic diagnostics of GPU are analyzed. It is noted that the most fruitful years of development of the methods of vibroacoustic diagnostics of GPUs are the 70-90s of the last century. Today, their development is taking place in the direction of using modern information technologies and various transformations in the processing of vibroacoustic processes to identify diagnostic signs of the technical state of the GPU.  The methods of diagnosing GPU type GTK-25i the analysis showed their absence. The exception is certain methods of their diagnostics based on modern information technologies, which were developed by the authors of the article. At the same time, the carried out improvement of the automatic control system (ACS) of the GPU type GTK-25i in terms of its technical and software makes it possible to obtain information about additional, in comparison with the standard ACS, technological parameters of the GPU type GTK-25i operation and vibroacoustic processes that accompany its operation. and can be used to create diagnostic methods for GPU type GTK-25i. The methodology for monitoring the technical condition of GPU type GTK-25i based on the determination of the highest values of the discriminant functions for each of the three technical states of GPU type GTK-25i for 16 technological parameters and acoustic and vibration characteristics is considered. At the same time, the best "nominal" condition is considered to be the state of GPU type GTK-25i after the repair work, the "defective" state "- before the repair work, and" current "- after the corresponding operating time of the GPU type GTK-25i. The use of the technique made it possible to develop a complex method, which is a combination of parametric and vibroacoustic diagnostics methods. It is shown that the use of the proposed method allows tracing the trend of changes in the technical state of GPU type GTK-25i in time and predicting the moment of its decommissioning. The developed method does not require additional technical means for its implementation, as it receives information from the improved ACS GPU type GTK-25i, which, in turn, can use the diagnostic results to control the gas compression process, taking into account the technical condition of the GPU type GTK-25i.  

Downloads

Download data is not yet available.

References

Zamikhovsky L.M., Saprykin S.O. The concept of monitoring the technical condition of gas pumping equipment. Visnyk Natsionalnoho technichnoho universytetu. 2009. No 8, Р. 64-68 [in Ukrainian].

Kunin P.S., Pavlenko P.P. Diagnostics of gas pumping units with centrifugal blowers. 2001. 362 p. [in Russian].

Grudz, V. Ya., Grudz, Ya. V., Kostiv, V.V. Technical diagnostics of pipeline systems. 2012. 512 p. [in Ukrainian].

Priymak K.O., Olynevych N.V., Dashchenko O.P. Pilot testing of the methodology for complex parametric identification of the actual characteristics of a power facility. 2015. No 1. Р. 47-54 [in Ukrainian].

Varlamov H. B., Priymak K.A. Algorithm for parametric identification of the actual characteristics of the gas-pumping unit of the compressor station. 2011. No 12 (94). Р. 10-13 [in Ukrainian].

Gerasimenko V.P. Algorithms for determining the main parameters of gas turbine gas compressor units in operation. 2009. No 3. Р. 116-121 [in Russian].

Wozniak M.P., Yurchilo T.V. Diagnostics of the technical condition of the gas compressor unit blower using the real operating parameters of its operation. 2012. No 2(32). Р. 215-221 [in Ukrainian].

Rybalko V.V. Parametric diagnostics of energy facilities based on factor analysis in the Statistica environment. 2004. No 2(6). Р. 78-83 [in Russian].

Kupreev E.I., Karnitsky N.B. Parametric diagnostics of gas pumping units. 2016. No 3(90). Р. 12-18 [in Russian].

Loboda I., Olivares Robles M.A. Gas turbine fault diagnosis using probabilistic neural networks. Int. J. Turbo Jet-Engines. 2015, No 32, Р. 175–191.

Early Fault Detection of Hot Components in Gas Turbines (Article) / L. Jinfu, L. Jiao, W. Jie [and other]. Journal of Engineering for Gas Turbines and Power. 2017. Volume 139, Issue 2, Article number 021201.

Zamikhovsky L.M., Pavlyk V.V. Investigation of the vibration state of an axial compressor GPU type GTK-25-i by "Nuovo Pigneone". 2014. No 1(32). Р. 28-38 [in Ukrainian].

Kochergin A.V., Pavlova N.V., Valeeva K.A. Vibroacoustic Control of Technical Conditions of GTE. Procedia Engineering Volume 150, 2016, Pages 363-369, 2nd International Conference on Industrial Engineering, ICIE 2016; Chelyabinsk; Russian Federation; 19 May 2016 through 20 May 2016; Code 123270 (Conference Paper) (Open Access).

Signal transforms for feature extraction from vibration signal for air compressor monitoring (Conference Paper) / N.K. Verma, R. Gupta, R.K. Sevakula, A. Salour. IEEE Region 10 Annual International Conference, Proceedings / TENCON Volume 2015 - January, 26 January 2015, Article number 70222752014 IEEE Region 10 Conference, TENCON 2014; Bangkok; Thailand; 22 October 2014 through 25 October 2014; Category number CFP14TEN-ART; Code 112841.

Yang W.S., Su Y.X., Chen Y.P. Air compressor fault diagnosis based on lifting wavelet transform and probabilistic neural network (Conference Paper). OP Conference Series: Materials Science and Engineering. 2019, Vol. 657, Issue 1, Article number 0120532nd International Conference on Numerical Modelling in Engineering, NME 2019; Beijing; China; 19 August 2019 through 22 August 2019; Code 153583. (Open Access).

Zamikhovskiy L., Zamikhovska O., Pavlyk V. Reseach of the characteristics of acoustic processes using wavelet transformation for detecting a diagnostic sign of the technical state of gas pumping units. TECHNOLOGY AUDIT AND PRODUCTION RESERVES, 2021. No 1/2(57). P. 6-12. DOI: 10.15587/2706-5448.2021.224432

Zamikhovsky L.M., Pavlyk V. V. Control of technical condition of gas pumping units on the basis of artificial neural networks. 2017. Р. 317-318 [in Ukrainian].

R Core Team R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. (2016). URL https://www.R-project.org/.

StatSoft, Inc. (2011). STATISTICA (data analysis software system), version 10. www.statsoft.com.

Published

2020-12-30

How to Cite

Zamikhovskyi, L. M., Zamikhovska, O. L., & Pavlyk, V. V. (2020). Methodology for monitoring the technical condition of GPU type GTK-25i in the process of operation. Scientific Bulletin of Ivano-Frankivsk National Technical University of Oil and Gas, (2(49), 106–116. https://doi.org/10.31471/1993-9965-2020-2(49)-106-116

Issue

Section

INFORMATION PROGRAMS AND COMPUTER-INTEGRATED TECHNOLOGIES