Fuzzy-Bayesian network for refrigeration compressor performance prediction and test time reduction

  • Authors:

  • Cesar A. Penz;Carlos A. Flesch;Silvia M. Nassar;Rodolfo C. C. Flesch;Marco A. de Oliveira

  • Affiliations:

  • Dep. de Engenharia Mecínica, Universidade Federal de Santa Catarina, POB 5053, 88040-970 Florianópolis, SC, Brazil;Dep. de Engenharia Mecínica, Universidade Federal de Santa Catarina, POB 5053, 88040-970 Florianópolis, SC, Brazil;Dep. de Informática e Estatística, Universidade Federal de Santa Catarina, 88040-900 Florianópolis, SC, Brazil;Dep. de Automação e Sistemas, Universidade Federal de Santa Catarina, 88040-900 Florianópolis, SC, Brazil;Whirlpool S.A., Unidade EMBRACO, 89219-901 Joinville, SC, Brazil

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

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Abstract

A typical characteristic of refrigeration compressor performance tests is their long duration. A reduction in the time periods related to this activity can be achieved using unsteady-state data analysis. This paper presents an original approach to predicting compressor performance using Bayesian networks and a hybrid Fuzzy-Bayesian network. All analysis was performed using real test data.