Correlative Method for Diagnosing Gas-Turbine Tribological Systems

Deliś, M.; Kłysz, S.; Przysowa, R. Correlative Method for Diagnosing Gas-Turbine Tribological Systems. Sensors 2023, 23, 5738. Deliś, M.; Kłysz, S.; Przysowa, R. Correlative Method for Diagnosing Gas-Turbine Tribological Systems. Sensors 2023, 23, 5738.

Abstract

Lubricated tribosystems such as main-shaft bearings in gas turbines have been successfully diagnosed by oil sampling for many years. In practice, the interpretation of wear debris analysis results can pose a challenge due to the intricate structure of power transmission systems and the varying degrees of sensitivity among test methods. In this work, oil samples acquired from the fleet of M601T turboprop engines were tested with optical emission spectrometry. Two-way analysis of variance (ANOVA) with interaction analysis and post hoc tests were carried out on measurement data from the whole fleet of the M-601T turboprop engines to study the impact of aluminum and zinc concentration on iron concentration. Finally, the developed model was used to evaluate the oil testing results for two specific engines of this type. Thanks to ANOVA, the assessment of engine health is based on a statistically proven correlation between the values of the dependent variable and the classifying factors.

Keywords

wear debris; oil analysis; emission spectroscopy; turboprop; propeller governor; ANOVA; interaction analysis; condition indicator

Subject

Engineering, Aerospace Engineering

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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