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Vibration analysis diagnostics by continuous-time models: A case study

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  • Pedregal, Diego J.
  • Carmen Carnero, Ma.

Abstract

In this paper a forecasting system in condition monitoring is developed based on vibration signals in order to improve the diagnosis of a certain critical equipment at an industrial plant. The system is based on statistical models capable of forecasting the state of the equipment combined with a cost model consisting of defining the time of preventive replacement when the minimum of the expected cost per unit of time is reached in the future. The most relevant features of the system are that (i) it is developed for bivariate signals; (ii) the statistical models are set up in a continuous-time framework, due to the specific nature of the data; and (iii) it has been developed from scratch for a real case study and may be generalised to other pieces of equipment. The system is thoroughly tested on the equipment available, showing its correctness with the data in a statistical sense and its capability of producing sensible results for the condition monitoring programme.

Suggested Citation

  • Pedregal, Diego J. & Carmen Carnero, Ma., 2009. "Vibration analysis diagnostics by continuous-time models: A case study," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 244-253.
    • Handle: RePEc:eee:reensy:v:94:y:2009:i:2:p:244-253
    DOI: 10.1016/j.ress.2008.03.003
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    References listed on IDEAS

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    1. Pedregal, Diego J. & Carmen Carnero, Ma, 2006. "State space models for condition monitoring: a case study," Reliability Engineering and System Safety, Elsevier, vol. 91(2), pages 171-180.
    2. Christer, A. H. & Wang, W. & Sharp, J. M., 1997. "A state space condition monitoring model for furnace erosion prediction and replacement," European Journal of Operational Research, Elsevier, vol. 101(1), pages 1-14, August.
    3. Myötyri, E. & Pulkkinen, U. & Simola, K., 2006. "Application of stochastic filtering for lifetime prediction," Reliability Engineering and System Safety, Elsevier, vol. 91(2), pages 200-208.
    4. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    5. Baker, R. D. & Christer, A. H., 1994. "Review of delay-time OR modelling of engineering aspects of maintenance," European Journal of Operational Research, Elsevier, vol. 73(3), pages 407-422, March.
    6. Scarf, Philip A., 1997. "On the application of mathematical models in maintenance," European Journal of Operational Research, Elsevier, vol. 99(3), pages 493-506, June.
    7. Christer, A. H. & Wang, W., 1995. "A simple condition monitoring model for a direct monitoring process," European Journal of Operational Research, Elsevier, vol. 82(2), pages 258-269, April.
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    Cited by:

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    2. Simeu-Abazi, Zineb & Lefebvre, Arnaud & Derain, Jean-Pierre, 2011. "A methodology of alarm filtering using dynamic fault tree," Reliability Engineering and System Safety, Elsevier, vol. 96(2), pages 257-266.

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