Skip to main content
Log in

Availability Assessment of Mounting Groups of Mining Machines

  • Science of Mining Machines
  • Published:
Journal of Mining Science Aims and scope

Abstract

The classification of the methods available for diagnostic of mining machinery mounting groups with roller bearings is considered with indicated advantages and disadvantages. The model is constructed to describe formation of shock pulses in roller bearings when different defects are generated in them. This model is suitable for the availability monitoring of the machinery mounting groups. The applicability of wavelet transforms instead of the standard fast Fourier transform to random processes and vibro-acoustic signals is tested for the detection of defects in manufacture and operation of mining machines.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Klyuev, V.V. (Ed.), Nerazrushayushchii kontrol’: spravochnik (Nondestructive Control: Handbook), Books 1 and 2, Moscow: Mashinostroenie, 2006.

    Google Scholar 

  2. Kukharenko B. G. Indirect Identification of Low-Pressure Compressor Blade Flutter with Oscillation Record Preprocessing in Use, Probl. Mashinost. Avtomatiz., 2008, no. 4, pp. 37–43.

    Google Scholar 

  3. Gerike, P.B. and Nesterova, O.A., Application of Nondestructive Tests Data to Creation of Identification Procedure for Technical State of Mining Equipment by Vibration Parameters, Vestn. KuzGTU, 2017, no. 6, pp. 161–169.

    Google Scholar 

  4. Gammershmidt, A.A., Coal Industry in Kuzbass: Current Conditions and Development Prospects, Ugol’, 2015, no. 5, pp. 14–15.

    Google Scholar 

  5. Galkin, V.I. and Sheshko, E.E., Transportnye mashiny (Transport Machines), Moscow: Gornaya kniga, 2010.

    Google Scholar 

  6. Gerike, B.L., Sushko, A.E., and Gerike, P.B., Introduction of Digital Technologies in the Field of Technical Diagnosis, Maintenance and Repair of Mining Machines and Equipment, Tekhnika Tekhnol. Gorn. Dela, 2018, no. 3, pp. 19–28.

    Google Scholar 

  7. Wu, J.D. and Liu, C.H., Investigation of Engine Fault Diagnosis Using Discrete Wavelet Transform and Neural Network, Expert Systems with Applications, 2008, vol. 35, pp. 1200–1213.

    Article  Google Scholar 

  8. Bendjama, H., Bouhouche, S., Boucherit, M.S., and Mansour, M., Vibration Signal Analysis Using Wavelet-PCA-NN Technique for Fault Diagnosis in Rotating Machinery, The Mediterranean J. of Measurement and Control, 2010, vol. 6, no. 4, pp. 145–154.

    Google Scholar 

  9. Zakharov, A.Y. and Shiryamov, D.B., Determination of Critical Rotational Resistance value of Conveyor Rollers, Gorn. Oborud. Elektrotekhn., 2016, no. 1, pp. 3–8.

    Google Scholar 

  10. Mamet’ev, L.E., Lyubimov, O.V., and Drozdenko, Yu.V., Justification of Technological Lifespan Parameters for Bearing Units of Augering Machines, Vestn. KuzGTU, 2013, no. 1 (95), pp. 16–18.

    Google Scholar 

  11. Krakovskii, Yu.M., Matematicheskie i programmnye sredstva otsenki tekhnicheskogo sostoyaniya oborudovaniya (Mathematical and Software Tools of Availability Evaluation of Equipment), Novosibirsk: Nauka, 2005.

    Google Scholar 

  12. Kelly S. Graham, Advanced Vibration Analysis, 2013.

    Google Scholar 

  13. Kapranov, B.I. and Korotkova, I.A., Spektral’nyi analiz v nerazrushayushchem kontrole (Spectral Analysis in Nondestructive Testing), Tomsk: TPU, 2010.

    Google Scholar 

  14. Klyuev, V.V. (Ed.), Nerazrushayushchii kontrol’: spravochnik (Nondestructive Control: Handbook), vol. 5, Moscow: Mashinostroenie, 2005.

  15. PC-Based Predictive Maintenance Systems CSI, Knoxville, TN 37923, USA.

  16. Shirman, A.R. and Solov’ev, A.B., Prakticheskaya vibrodiagnostika i monitoring sostoyaniya mekhanicheskogo oborudovaniya (Applied Vibration Diagnostics and Monitoring of Mechanical Equipment), Moscow, 1996.

    Google Scholar 

  17. Bearing Failure Diagnosis, NSK Motion & Control, 2009.

    Google Scholar 

  18. Bearing Damages and Their Causes, SKF AB, 2002.

    Google Scholar 

  19. Rudloff, L., Arghir, M., Bonneau, O., Guingo, S., Chemla, G., and Renard, E., Experimental Analysis of the Dynamic Characteristics of a Hybrid Aerostatic Bearing, J. Eng. for Gas Turbines and Power, 2012, vol. 134, no. 18.

    Google Scholar 

  20. Sal’nikov, A.F., Vibroakusticheskaya diagnostika tekhnicheskikh ob’ektov (Vibro-Acoustic Diagnosis of Engineering Objects), Perm: PNIPU, 2011.

    Google Scholar 

  21. Astaf’eva, N.M., Wavelet Analysis: New Theories and Application Examples, Usp. Fiz. Nauk, 1996, vol. 166, no. 11, pp. 1145–1170.

    Article  Google Scholar 

  22. Vityazev, V.V., Veivlet-analiz vremennykh ryadov (Wavelet Analysis of Time Series), Saint-Petersburg: SPbGU, 2001.

    Google Scholar 

  23. D’yakonov, V.P., MATLAB: polnyi samouchitel’ (MATLAB: Complete Self-Teaching Textbook), Saint-Petersburg: DMK Press, 2012.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to B. L. Gerike or A. A. Mokrushev.

Additional information

Russian Text © The Author(s), 2019, published in Fiziko-Tekhnicheskie Problemy Razrabotki Poleznykh Iskopaemykh, 2019, No. 6, pp. 106-114.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gerike, B.L., Klishin, V.I. & Mokrushev, A.A. Availability Assessment of Mounting Groups of Mining Machines. J Min Sci 55, 954–961 (2019). https://doi.org/10.1134/S1062739119066344

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1062739119066344

Keywords

Navigation