Evaluation method of allowable variance for results of tribological measurement on the basis of their the coherence trends and of the covariance trends

Zboiński, Marek; Lindstedt, Paweł; Deliś, Maciej

doi:10.1515/jok-2015-0052

Cited by 2 publications

(1 citation statement)

References 2 publications

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“…Pair-wise analytical techniques such as correlation [ 20 , 21 , 22 ] or regression are widespread in oil analysis because relying on a single parameter may not provide reliable solutions and may also overlook significant diagnostic information. Correlation describes a statistical relationship between two random variables.…”

Section: Introductionmentioning

confidence: 99%

Correlative Method for Diagnosing Gas-Turbine Tribological Systems

Deliś

Kłysz

Przysowa

2023

Sensors

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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 and analyzed with a correlative model. Customized alarm limits were determined for iron by binning aluminum and zinc concentration into four levels. Two-way analysis of variance (ANOVA) with interaction analysis and post hoc tests was carried out to study the impact of aluminum and zinc concentration on iron concentration. A strong correlation between iron and aluminum, as well as a weaker but still statistically significant correlation between iron and zinc, was observed. When the model was applied to evaluate a selected engine, deviations of iron concentration from the established limits indicated accelerated wear long before the occurrence of critical damage. Thanks to ANOVA, the assessment of engine health was based on a statistically proven correlation between the values of the dependent variable and the classifying factors.

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Section: Introductionmentioning

confidence: 99%

Correlative Method for Diagnosing Gas-Turbine Tribological Systems

Deliś

Kłysz

Przysowa

2023

Sensors

Self Cite

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Correlative Method for Diagnosing Gas-Turbine Tribological Systems

Deliś¹,

Kłysz²,

Przysowa³

2023

Preprint

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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.

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Evaluation method of allowable variance for results of tribological measurement on the basis of their the coherence trends and of the covariance trends

Cited by 2 publications

References 2 publications

Correlative Method for Diagnosing Gas-Turbine Tribological Systems

Correlative Method for Diagnosing Gas-Turbine Tribological Systems

Correlative Method for Diagnosing Gas-Turbine Tribological Systems

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