- Research Article
- 10.1021/acsomega.5c08478
Integrated Mechanicaland Chemical Diagnostics forEngine Health Monitoring Using Biodiesel Blends
- Jan 27, 2026
- ACS Omega
- Jitendra Yadav + 6 more +6
The transition to renewable fuels necessitates reliablediagnostictools for monitoring engine health and lubricant stability. This studyintroduces an integrated methodology that combines vibration signatureanalysis with oil degradation indices to evaluate the long-term performanceof a single-cylinder diesel engine operated with Jatropha-based biodieselblends (10%, 20%, and 30% v/v). Over 100 h (h) of operation, vibrationdata were recorded using fast Fourier transform analysis, while oilcondition was monitored through viscosity, density, and infrared spectroscopyto quantify soot, oxidation, nitration, sulfation, and additive depletion.Statistical evaluation, including Pearson correlation, revealed stronginterdependencies between vibration amplitude and chemical degradationmarkers, confirming a direct mechanical–chemical linkage. Amongall blends, the 20% biodiesel blend exhibited the most favorable performance,showing the lowest vibration amplitude, minimal additive depletion,and stable physicochemical oil properties, thereby aligning closelywith baseline diesel. These findings establish a novel dual-parameterdiagnostic framework for predictive maintenance, offering significantpotential for extending the lubricant life, reducing downtime, andsupporting the adoption of sustainable biodiesel in compression ignitionengines. To the best of our knowledge, this is the first study todirectly correlate vibration signatures with FTIR-based oil degradationindices to establish a dual-parameter predictive diagnostic frameworkfor biodiesel-fueled engines. The study also develops a regression-basedpredictive model (R2 = 0.81, p < 0.05) linking vibration amplitude with oxidation and viscosityindices, establishing a foundation for real-time predictive maintenanceapplications.
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