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″,...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-09-01
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Series: | Lubricants |
Subjects: | |
Online Access: | https://www.mdpi.com/2075-4442/11/9/382 |