Abstract:
Contamination via fuel dilution can result in degradation of the engine oil which could lead to
increased engine wear and/or engine failure. Exposing lubricant contamination by fuel dilution can
involve a multi-parametric evaluation while undertaking lubricant condition monitoring also known as
used oil analysis (UOA). We utilize hierarchical cluster analysis to extricate the contamination related
parameters caused by fuel dilution in the medium speed engine lubricant. Cluster analysis classifies
several objects into some cluster according to the similarities between them but the results are
uncertain due to sampling error of the data. We address this by evaluating the probability values (pvalues) for each cluster, while Cluster validity is ensured by using a module to offer the best
clustering scheme among different results. The result of the cluster analysis is analysed using expert
assessment and literature to pick out the effects of fuel dilution contamination in a lubricant used in a
medium speed engine. This methodology is applied to thermal power plant UOA case study. The
novelty of the study is firstly, exposing the used oil parameters associated with fuel dilution using
hierarchical clustering, secondly, assessment of the uncertainty of the hierarchical cluster developed,
thirdly, use of expert assessment to confirm the cluster relationship developed as well as the effects
of this contamination to the performance and integrity of the engine, and lastly provide insights for
maintenance decision making and moreover, highlighting critical used oil analysis parameters that
are correlated which are indicative of degradation via fuel contamination. By addressing such
related parameters in UOA, organizations can better enhance the reliability of critical operable
equipment like engines
