Vibration diagnostics of machine friction units: analysis of the current state and prospects

Authors

  • O. Lytvynov Khmelnitskyi National University
  • O. Dykha Khmelnitskyi National University

DOI:

https://doi.org/10.31891/2079-1372-2023-110-4-44-51

Keywords:

wear, friction details, vibrations, diagnosis, repair, forecasting

Abstract

Vibration diagnostics makes it possible to detect defects in the friction parts of the machine at the early stages of their development, which provides for the repair or replacement of parts before they fail. In this work, an analysis of modern research on the use of vibration diagnostics in tribology is carried out, which includes aspects: vibration diagnostics in technology and tribology; vibration during friction and wear; vibration assessment methods; theoretical approaches in the analysis and modeling of vibrations. It is noted that an important aspect is the development and implementation of theoretical approaches in the analysis and modeling of vibrations, which allows a deeper understanding of the dynamics of friction and wear. This approach makes it possible to develop accurate and adaptive strategies for maintenance and optimization of tribotechnical parameters. It is shown that vibration diagnostics is not only a tool for detecting malfunctions, but also a key element for ensuring the long-term and efficient functioning of friction units of machines. The effective use of vibration diagnostics can significantly reduce maintenance costs, increase the reliability and productivity of equipment, which becomes an indispensable condition for the effective functioning of modern technical systems.

References

Jour Tang, Gang Mohd Ghazali, Mohamad Hazwan Rahiman, Wan Hindawi, Vibration Analysis for Machine Monitoring and Diagnosis: A Systematic Review 2021/09/11.https://doi.org/10.1155/2021/9469318

Z. Peng, N. Kessissoglou, An integrated approach to fault diagnosis of machinery using wear debris and vibration analysis, Wear, Volume 255, Issues 7–12, 2003, Pages 1221-1232, ISSN 0043-1648.https://doi.org/10.1016/S0043-1648(03)00098-X

Purushottam Gangsar, Rajiv Tiwari, Signal based condition monitoring techniques for fault detection and diagnosis of induction motors, Mechanical Systems and Signal Processing, Volume 144, 2020, 106908, ISSN 0888-3270.https://doi.org/10.1016/j.ymssp.2020.106908

AP Bovsunovsky, Efficiency analysis of vibration-based crack diagnostics in rotating shafts, Engineering Fracture Mechanics, Volume 173, 2017, Pages 118-129, ISSN 0013-7944. https://doi.org/10.1016/j.engfracmech.2017.01.014.

Hoon Sohn, Charles R Farrar, Damage diagnosis using time series analysis of vibration signals, 2001/06/01 https://dx.doi.org/10.1088/0964-1726/10/3/304

RA Ibrahim,Friction-Induced Vibration, Chatter, Squeal, and Chaos—Part I: Mechanics of Contact and Friction,Appl. Mech. Rev. Jul 1994, 47(7): 209-226 (18 pages). https://doi.org/10.1115/1.3111079

Mohammad Asaduzzaman Chowdhury, Md. Maksud Helali, The effect of frequency of vibration and humidity on the coefficient of friction, Tribology International, Volume 39, Issue 9, 2006, Pages 958-962, ISSN 0301-679X.

Thomas Skåre, Jan-Eric Ståhl, Static and dynamic friction processes under the influence of external vibrations, Wear, Volume 154, Issue 1, 1992, Pages 177-192, ISSN 0043-1648.https://doi.org/10.1016/0043-1648(92)90253-5

Łubiński, J., Druet, K., The Application of Vibration Recording and Analysis in Tribological Research on Sliding Friction, In: Timofiejczuk, A., Łazarz, BE, Chaari, F., Burdzik, R. (eds) Advances in Technical Diagnostics. ICTD 2016. Applied Condition Monitoring, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-62042-8_19

Aral Sarrafi, Zhu Mao, Christopher Niezrecki, Peyman Poozesh, Vibration-based damage detection in wind turbine blades using Phase-based Motion Estimation and motion magnification, Journal of Sound and Vibration, Volume 421, 2018, Pages 300-318, ISSN 0022-460X. https://doi.org/10.1016/j.jsv.2018.01.050

Cong Peng, Haining Gao, Xiaoyue Liu, Bin Liu, A visual vibration characterization method for intelligent fault diagnosis of rotating machinery, Mechanical Systems and Signal Processing, Volume 192, 2023, 110229, ISSN 0888-3270. https://doi.org/10.1016/j.ymssp.2023.110229

N Tandon, A Choudhury, A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings, Tribology International, Volume 32, Issue 8, 1999, Pages 469-480, ISSN 0301-679X. https://doi.org/10.1016/S0301-679X(99)00077-8

Tuncay Karacay, Nizami Akturk, Experimental diagnostics of ball bearings using statistical and spectral methods, Tribology International, Volume 42, Issue 6, 2009, Pages 836-843, ISSN 0301-679X. https://doi.org/10.1016/j.triboint.2008.11.003

Lingli Cui, Yu Zhang, Feibin Zhang, Jianyu Zhang, Seungchul Lee, Vibration response mechanism of faulty outer race rolling element bearings for quantitative analysis, Journal of Sound and Vibration, Volume 364, 2016, Pages 67-76, ISSN 0022- 460X. https://doi.org/10.1016/j.jsv.2015.10.015

Aoyu Chen, Thomas R. Kurfess, Signal processing techniques for rolling element bearing spall size estimation, Mechanical Systems and Signal Processing, Volume 117, 2019, Pages 16-32, ISSN 0888-3270. https://doi.org/10.1016/j.ymssp.2018.03.006

GX Chen, ZR Zhou, Time–frequency analysis of friction-induced vibration under reciprocating sliding conditions, Wear, Volume 262, Issues 1–2, 2007, Pages 1-10, ISSN 0043-1648. https://doi.org/10.1016/j.wear.2006.03.055

Hoon Sohn, Charles R Farrar, Damage diagnosis using time series analysis of vibration signals, Smart Mater. Struct. 10 446, 2001/06/01 https://dx.doi.org/10.1088/0964-1726/10/3/304

Qi Zhuge, Yongxiang Lu, Shichao Yang, Non-stationary modeling of vibration signals for monitoring the condition of machinery, Mechanical Systems and Signal Processing, Volume 4, Issue 5, 1990, Pages 355-365, ISSN 0888-3270. https://doi.org/10.1016/0888-3270(90)90020-L

J. Antoni, F. Bonnardot, A. Raad, M. El Badaoui, Cyclostationary modeling of rotating machine vibration signals, Mechanical Systems and Signal Processing, Volume 18, Issue 6, 2004, Pages 1285-1314, ISSN 0888-3270 . https://doi.org/10.1016/S0888-3270(03)00088-8

C. Capdessus, M. Sidahmed, Jl lacoume, Cyclostationary processes: application in gear faults early diagnosis, Mechanical Systems and Signal Processing, Volume 14, Issue 3, 2000, Pages 371-385, ISSN 0888-3270. https://doi.org/10.1006/mssp.1999.1260.

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Published

2023-12-18

How to Cite

Lytvynov, O., & Dykha, O. (2023). Vibration diagnostics of machine friction units: analysis of the current state and prospects. Problems of Tribology, 28(4/110), 44–51. https://doi.org/10.31891/2079-1372-2023-110-4-44-51

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