Abstract

PINO GOMEZ, Joel; HERNANDEZ MONTERO, Fidel E.  and  GOMEZ MANCILLA, Julio Cesar. Variables selection for journal bearing fault diagnostic.. Rev cuba cienc informat [online]. 2018, vol.12, n.4, pp. 41-51. ISSN 2227-1899.

Experts in diagnostic can provide essential information, expressed in mixed variables (quantitative and qualitative), about journal bearing faults, nevertheless feature selection researches for fault diagnostic applications forget this important knowhow. This work is focused to identify the most important features for fault identification in a steam turbine journals bearings. The values sets that support this research come from stored diagnostics and maintenance reports of an active thermoelectric power plant. Mixed data processing was accomplished by mean of logical combinatorial pattern recognition tools. Confusion of raw features set was obtained employing different comparison criteria’s. Subsequently was identified the testor and typical testor and compute the informational weight of features that conform typical testor. The values of the mixed features originated by expert knowledge are shown through the obtained results.

Keywords : confusion; features; mixed; selecticon; testor.

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