Unlocking the Potential of Soft Computing for Predicting Lubricant Elemental Spectroscopy

Unlocking the Potential of Soft Computing for Predicting Lubricant Elemental Spectroscopy

Predictive maintenance of mechanical systems relies on accurate condition monitoring of lubricants. This study assesses the performance of soft computing models in predicting the elemental spectroscopy (Fe, Pb, Cu, Cr, Al, Si, and Zn) of engine lubricants, based on the electrical properties (ε′, ε″,...

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Bibliographic Details
Main Authors: Mohammad-Reza Pourramezan, Abbas Rohani, Mohammad Hossein Abbaspour-Fard
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Lubricants
Subjects:
soft computing models
condition-based maintenance
lubricant condition monitoring
dielectric spectroscopy
Online Access:https://www.mdpi.com/2075-4442/11/9/382

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