Aviation lubricating oil, as the “blood of machine operation”, plays an important role in the
lubrication, cooling, cleaning, sealing, rust prevention, and other aspects of aero‐engines …

The viability of employing soft computing models for predicting the viscosity of engine
lubricants is assessed in this paper. The dataset comprises 555 reports on engine oil …

Lubricant condition diagnosis often encounters conflicting conclusions due to the reverse
degradation of indicators and coupling failures. To address this issue, a knowledge-guided …

Abstract Machine learning is presently receiving great attention. However, machine learning
applications to gasoline engine research are limited. This paper investigated the …

The statistical relationship between sensor signature features and lubricant solid particle
contamination conditions in a spherical roller bearing has been investigated in this study …

This study investigates the influence of six metallic and non-metallic elements (Fe, Cr, Pb,
Cu, Al, Si) on the quality of engine oil under normal, cautious, and critical conditions. To …

This study addresses the integration of machine learning (ML) with supervisory control and
data acquisition (SCADA) systems to enhance predictive maintenance and operational …

Thermally stable lubricants are vital in industries grappling with high temperatures that affect
lubrication systems. Crafted with premium base oils and additives, they endure exposure to …

Integrating bio-lubricants into internal combustion engines is crucial for sustainable
engineering, driven by the need for renewable and eco-friendly alternatives. However, bio …

Artificial intelligence (AI) and machine learning (ML) have been the subjects of increased
interest in recent years due to their benefits across several fields. One sector that can benefit …