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Novel Techniques of Diagnostic Data Processing for Belt Conveyor Maintenance

  • Radoslaw ZimrozEmail author
  • Paweł K. Stefaniak
  • Walter Bartelmus
  • Monika Hardygóra
Part of the Lecture Notes in Production Engineering book series (LNPE)

Abstract

In the paper a new diagnostic approach for gearbox used in belt conveyors will be discussed. The purpose of the work is to provide novel view on diagnostic data processing in the context of detection of changes in condition for population of gearboxes used in belt conveyor network. The idea will be presented by examples: a data base of diagnostic features collected during last 3 years (real data from conveyors operating in mining company) will be used for illustration.

The method takes advantage from recent results of research carried out by authors and other researchers related to different types of gearboxes used in mining and other machines, (i.e. belt conveyors, bucket wheel excavators, coal shearers, wind turbines and helicopters). A serious dependency between diagnostic features and operational conditions (speed/load) it is shown in mentioned works.

A novel research hypothesis has been formulated that behavior of machine in bad condition is unstable and it is more visible for heavy loaded machine.

It results with diagnostic data set with higher data dispersion than for healthy one. In the paper we will prove that feature load dependency and data dispersion might be a basis for novel approach for condition monitoring of gearboxes used in belt conveyors. An advantage of such approach is its simplicity and strong physical background.

Keywords

belt conveyor diagnostics novel features data processing 

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References

  1. 1.
    Bartelmus, W., Zimroz, R.: A new feature for monitoring the condition of gearboxes in non-stationary operating conditions. Mech. Syst. and Signal Proc. 23, 1528–1534 (2009)CrossRefGoogle Scholar
  2. 2.
    Zimroz, R., Bartelmus, W., Barszcz, T., Urbanek, J.: Diagnostics of bearings in presence of strong operating conditions non-stationarity-A procedure of load-dependent features processing with application to wind turbine bearings. Mechanical Systems and Signal Processing (2013), doi:10.1016/j.ymssp.2013.09.010Google Scholar
  3. 3.
    Bellino, A., Fasana, A., Garibaldi, L., Marchesiello, S.: PCA-based detection of damage in time-varying systems. Mechanical Systems and Signal Processing 24(7), 2250–2260 (2010)CrossRefGoogle Scholar
  4. 4.
    Zimroz, R., Bartkowiak, A.: Two simple multivariate procedures for monitoring planetary gearboxes in non-stationary operating conditions. Mechanical Systems and Signal Processing 38(1), 237–247 (2013)CrossRefGoogle Scholar
  5. 5.
    Kacprzak, M., Kulinowski, P., Wedrychowicz, D.: Computerized information system used for management of mining belt conveyors operation. Eksploatacja i Niezawodnosc – Maintenance and Reliability 50(2), 81–93 (2011)Google Scholar
  6. 6.
    Lodewijks, G.: Strategies for Automated Maintenance of Belt Conveyor Systems. Bulk Solids Handling 24(1), 16–22 (2004)Google Scholar
  7. 7.
    Zimroz, R., Krol, R., Hardygora, M., Gorniak-Zimroz, J., Bartelmus, W., Gladysiewicz, L., Biernat, S.: A maintenance strategy for drive units used in belt conveyors network. In: Eskikaya, Ş. (ed.) 22nd World Mining Congress & Expo, Istanbul, September 11-16, vol. 1, pp. 433–440. Aydoğdu of set, Ankara (2011)Google Scholar
  8. 8.
    Galar, D., Gustafson, A., Tormos, B., Berges, L.: Maintenance Decision Making based on Different types of Data Fusion. Eksploatacja i Niezawodnosc – Maintenance and Reliability 14(2), 135–144 (2012)Google Scholar
  9. 9.
    Cempel, C.: Limit value in practice of vibration diagnosis. Mechanical Systems and Signal Processing 4(6) (1990)Google Scholar
  10. 10.
    Brooks, R., Thorpe, R., Wilson, J.: A new method for defining and managing process alarms and for correcting process operation when an alarm occurs. Journal of Hazardous Materials 115 (2004)Google Scholar
  11. 11.
    Jablonski, A., Barszcz, T., Bielecka, M., Breuhaus, P.: Modeling of probability distribution functions for automatic threshold calculation in condition monitoring systems. Measurement 46(1), 727–738 (2013)CrossRefGoogle Scholar
  12. 12.
    Bartelmus, W.: Gearbox damage process. J. Phys.: Conf. Ser. 305(1), paper no 012029 (2011), doi:10.1088/1742-6596Google Scholar
  13. 13.
    Bartelmus, W., Chaari, F., Zimroz, R., Haddar, M.: Modelling of gearbox dynamics under time-varying nonstationary load for distributed fault detection and diagnosis. European Journal of Mechanics. A, Solids 29(4), S.637–S.646 (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Radoslaw Zimroz
    • 1
    • 2
    Email author
  • Paweł K. Stefaniak
    • 1
  • Walter Bartelmus
    • 1
  • Monika Hardygóra
    • 1
    • 2
  1. 1.Diagnostics and Vibro-Acoustics Science LaboratoryWroclaw University of TechnologyWroclawPoland
  2. 2.KGHM Cuprum Ltd., Research & Development CentreWroclawPoland

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