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Lubricants
Special Issues
Condition Monitoring of Lubricating Oils
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Condition Monitoring of Lubricating Oils

A special issue of Lubricants (ISSN 2075-4442).

Deadline for manuscript submissions: 31 May 2026 | Viewed by 1199

Special Issue Editor

Prof. Dr. Surapol Raadnui

E-Mail Website
Guest Editor
Department of Production Engineering, Faculty of Engineering, King Mongkut's University of Technology North Bangkok (KMUTNB), 1518 Pracharaj 1, Bangsue, Bangkok 10800, Thailand
Interests: used lubricant analysis; maintenance tribology

Special Issue Information

Dear Colleagues,

Used lubricant analysis plays a pivotal role in the condition monitoring of oil- and grease-lubricated machinery. By assessing degradation, contamination, and wear signatures in service, lubricant analysis provides valuable data to support predictive and proactive maintenance strategies.

This Special Issue of Lubricants seeks contributions focusing on innovative research and industrial applications of used lubricant analysis. We encourage submissions on sensor-based techniques, such as capacitive, acoustic, and optical sensing, for real-time oil condition assessment. Papers detailing spectrometric and ferrographic analysis for monitoring wear metals, contaminants, and additive depletion are also welcome.

We are particularly interested in studies applying machine learning or statistical models to predict equipment health or remaining useful life (RUL) based on lubricant data. Comparative studies between grease and oil monitoring methods, and field applications in sectors like energy, manufacturing, and transportation, will provide valuable insight.

Additionally, research exploring lubricant degradation behavior, formulation–performance relationships, and environmentally sustainable lubricant usage aligns well with the Special Issue’s goals.

This Special Issue aims to bridge academic research and industrial practice, offering a platform for multidisciplinary work that improves machine reliability through lubricant-based diagnostics. Submissions demonstrating both technical rigor and application relevance will be prioritized.

Prof. Dr. Surapol Raadnui
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Lubricants is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • used lubricant analysis
  • wear debris monitoring
  • oil condition sensors
  • predictive/proactive/prognosis maintenance
  • machine learning diagnostics
  • grease and oil degradation

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Published Papers (3 papers)

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Research

14 pages, 3658 KB  
Article
Rheological Study and FTIR Analysis of Thermally Degraded Mineral and Biodegradable Hydraulic Fluids
by Andreea Mirela Teleașă, Nicolae-Alexandru Stoica, Alexandru Valentin Rădulescu, Sorin Cănănău, Ludmila Motelica and Radu Iulian Rădoi
Lubricants 2025, 13(10), 462; https://doi.org/10.3390/lubricants13100462 - 21 Oct 2025
Abstract
In this work, three hydraulic fluids—a paraffinic mineral hydraulic oil (H46) and two biodegradable oils (HETG46—hydraulic oil based on natural esters and HF-E46—hydraulic oil based on synthetic esters derived from fatty acids extracted from vegetable oils)—were studied in both fresh and thermally degraded [...] Read more.
In this work, three hydraulic fluids—a paraffinic mineral hydraulic oil (H46) and two biodegradable oils (HETG46—hydraulic oil based on natural esters and HF-E46—hydraulic oil based on synthetic esters derived from fatty acids extracted from vegetable oils)—were studied in both fresh and thermally degraded states. The study of these oils was performed both from a rheological and spectroscopic point of view using Fourier transform infrared spectroscopy (FTIR). The thermal degradation process consisted of repeated heating and cooling cycles at four different temperatures for 15 min performed eight times. The rheological characterization was initially performed for the fresh oils, and the results obtained were compared with those of the thermally degraded samples. For the rheological characterization, two rheological models (the Newtonian model and the power law model) were used, following which the rheological parameters were determined. At the same time, this work highlights how thermal degradation influences the rheological behavior and chemical structure of hydraulic fluids. The results obtained showed that the Newtonian model best describes the rheological behavior of the analyzed fluids. From a chemical point of view, FTIR analysis did not reveal significant changes between fresh fluids and those subjected to thermal degradation. Full article
(This article belongs to the Special Issue Condition Monitoring of Lubricating Oils)
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13 pages, 1251 KB  
Article
A Multi-Parameter-Driven SC-ANFIS Framework for Predictive Modeling of Acid Number Variations in Lubricating Oils
by Yawen Wang, Haijun Wei and Daping Zhou
Lubricants 2025, 13(10), 458; https://doi.org/10.3390/lubricants13100458 - 20 Oct 2025
Abstract
The acid number is widely recognized as one of the most essential and frequently used indicators for evaluating the degradation state of lubricants. Changes in acid number serve as a direct reflection of the oil’s oxidative deterioration. Conventional prediction methods, however, often neglect [...] Read more.
The acid number is widely recognized as one of the most essential and frequently used indicators for evaluating the degradation state of lubricants. Changes in acid number serve as a direct reflection of the oil’s oxidative deterioration. Conventional prediction methods, however, often neglect the coupling effects among multiple physical factors and lack sufficient dynamic adaptability. Therefore, this study proposes a method for predicting the variation trend of lubricating oil acid number by integrating an Adaptive Neuro-Fuzzy Inference System (ANFIS) with Subtractive Clustering (SC), establishing an SC-ANFIS-based predictive model. The subtractive clustering technique automatically determines the number of fuzzy rules and initial parameters directly from the dataset, thereby eliminating redundant rules and simplifying the model architecture. The SC-ANFIS model further optimizes the parameters of the fuzzy inference system through the self-learning ability of neural networks. Lubricant aging tests were conducted using a laboratory oxidation stability tester. Regular sampling was carried out to acquire comprehensive lubricant performance degradation data. The input variables of the model include the current acid number, carbonyl peak intensity, metal element concentrations (Fe and Cu), viscosity, and water content of the lubricating oil, while the output variable corresponds to the rate of change in the acid number of the lubricating oil relative to the previous time step. The proposed model demonstrates effective prediction of the lubricating oil acid number variation trend. Posterior difference tests confirmed its high predictive accuracy, with all three evaluation metrics—RMSE, MAE, and MAPE—outperforming those of the BP model. Full article
(This article belongs to the Special Issue Condition Monitoring of Lubricating Oils)
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25 pages, 1345 KB  
Article
Analysis of the MSD, ICF Function, G’ and G” Modulus and Raman and FTIR Spectroscopy Spectra to Explain Changes in the Microstructure of Vegetable Lubricants
by Rafal Kozdrach and Pawel Radulski
Lubricants 2025, 13(9), 416; https://doi.org/10.3390/lubricants13090416 - 16 Sep 2025
Viewed by 457
Abstract
This paper presents the results of a rheological and spectral study characterising the change in the microstructure of lubricants depending on the type of vegetable oil base. The three lubricating compositions were prepared based on vegetable oils (rapeseed, sunflower and abyssinian), where amorphous [...] Read more.
This paper presents the results of a rheological and spectral study characterising the change in the microstructure of lubricants depending on the type of vegetable oil base. The three lubricating compositions were prepared based on vegetable oils (rapeseed, sunflower and abyssinian), where amorphous silica of a specific particle size was used as a thickener. These three lubricating compositions were then modified by introducing the AW/EP additive (BCH 351) into their structure. Rheological tests were performed for the prepared lubricating compositions on a DWS diffusion spectrometer. Based on the tests, the dependence of ICF function values on time, MSD function values on time and G’ and G” modulus values on frequency were determined. From the collected data, rheological parameters such as the elasticity coefficient, MSD curve slope factor, diffusion coefficients and the value at which the G’ and G” curves intersect were determined, which characterise the microstructure of the tested lubricants. Raman and FTIR spectra were also performed to characterise the chemical structure of the compositions studied, and the intensity of integration of characteristic bands of vegetable greases was calculated. For vegetable greases made from different vegetable oils, a change in the value of the MSD function was observed, and the calculated value of the elasticity index indicates better viscoelastic properties for the grease made from rapeseed oil. Modification of vegetable greases with a multifunctional additive leads to a change in rheological parameters, indicating a change in the structure of the greases studied. The results of tests of diffusion coefficients for vegetable greases show a change in microstructure for greases made with different vegetable oils. Such results testify to moderately strong viscoelastic properties, leading to the conclusion that the produced greases are substances stable to changes in chemical structure depending on the base oil and modifying additive used. Raman and FTIR spectroscopy is a technique that enables changes in the chemical composition of vegetable oils to be assessed by analysing the degree of unsaturation of fatty acids in vegetable oils, making it a very good diagnostic method for quality control of lubricants based on vegetable oils. The results obtained make it possible to differentiate lubricants prepared with different vegetable oils and allow the chemical structure of the vegetable lubricants studied to be assessed on the basis of the intensity of integration of characteristic bands. Full article
(This article belongs to the Special Issue Condition Monitoring of Lubricating Oils)
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