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Optical Attenuation Characterization of Water Contaminated Lubricating Grease
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0002-4857-9475
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0003-3995-8331
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.ORCID iD: 0000-0003-4879-8261
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
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2018 (English)In: Tribology Transactions, ISSN 1040-2004, E-ISSN 1547-397X, Vol. 61, no 4, p. 726-732Article in journal (Refereed) Published
Abstract [en]

Water-contaminated grease samples are investigated with attenuation spectra in the visible and near-infrared (NIR) regions in this article. The purpose of this investigation was to identify a model with optical attenuation spectra such that the water content of grease samples could be characterized with a simple measurement setup using common methodology from the field of instrumental chemistry. The ratio between two chosen wavelengths of light appears to approximate the water content of grease samples with an acceptable coefficient of determination using a methodology to show what can potentially be done to develop condition monitoring tools. To illustrate the outlined method, a prestudy of grease aging and oxidation levels is also investigated to show that other variables do not significantly change the measurement.

Place, publisher, year, edition, pages
Taylor & Francis, 2018. Vol. 61, no 4, p. 726-732
National Category
Tribology (Interacting Surfaces including Friction, Lubrication and Wear) Applied Mechanics
Research subject
Machine Elements; Experimental Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-67205DOI: 10.1080/10402004.2017.1404175ISI: 000438157400015Scopus ID: 2-s2.0-85044094152OAI: oai:DiVA.org:ltu-67205DiVA, id: diva2:1172303
Note

Validerad;2018;Nivå 2;2018-08-09 (rokbeg)

Available from: 2018-01-09 Created: 2018-01-09 Last updated: 2019-09-14Bibliographically approved
In thesis
1. Sensors for Water Contamination in Lubricating Grease
Open this publication in new window or tab >>Sensors for Water Contamination in Lubricating Grease
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The purpose of this dissertation is to summarize the research carried out that led to the development of measurement techniques which measure the water content of lubricating grease. Calcium sulphonate complex (CaS-X) grease was used in all experiments for Papers A through E, with some additional greases used in Paper D.

A simple and effective grease mixing method for preparing grease samples was developed and tested for repeatability. The water content of these samples was also tested with time and temperature as added variables to study if and how much water will evaporate from the samples.

Additionally, three measurement principles were investigated: optical attenuation in the visible and near-infrared (NIR) region, a dielectric measurement method, and a galvanic current method.

The optical attenuation investigation found that the attenuation ratio of two wavelengths of light appear to approximate the water content of grease samples with an acceptable coefficient of determination. Additionally, aged and oxidized grease samples were measured in the experiment and were not found to affect the measurement results. The dielectric method uses the temperature dependence on the dielectric properties of water-contaminated grease to approximate the water content of the grease samples. An additional parameter of incomplete fill/coverage of the sensor has been investigated as a prestudy. The dielectric method was further optimized with computer automated measurements where an improved and miniaturized sensor was developed and used. A different method using the galvanic current between two different metals from the galvanic series was used to estimate water content as well. All three methods were found to provide measurements of water content in the prepared grease samples (ranging from 0.22% to 5.5% added water). The dielectric measurement is likely going to be better for applications requiring the possibility of measuring a larger bulk of the grease within the bearing, with the capability of using several different configurations of sensors for different types of bearings and applications. It shows promise for providing an accurate and robust system for monitoring grease condition as well as the amount of grease contained. The optical measurement will likely provide additional information; however, it will only measure small point samples within the bearing instead of the larger bulk. This could be of use though, because the sensors could be small (in the several millimeter scale) and could measure where water damage is determined to be most important to detect at. The galvanic current method was also found to provide a useful correlation to water content but may provide additional information about how corrosive the grease has become, indirectly estimating the water content.

The research contained herein has shown promise for future development for developing new grease condition monitoring tools. The optical, dielectric, and galvanic methods have their own unique challenges and may provide useful information in different applications, or perhaps be used in conjunction with each other to provide a more complete diagnostic tool.

Place, publisher, year, edition, pages
Luleå University of Technology, 2019. p. 200
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
National Category
Reliability and Maintenance Tribology (Interacting Surfaces including Friction, Lubrication and Wear)
Research subject
Experimental Mechanics
Identifiers
urn:nbn:se:ltu:diva-75998 (URN)978-91-7790-439-7 (ISBN)978-91-7790-440-3 (ISBN)
Public defence
2019-11-04, D770, Luleå, 10:00 (English)
Opponent
Supervisors
Available from: 2019-09-16 Created: 2019-09-14 Last updated: 2019-10-16Bibliographically approved

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Dittes, NicholasPettersson, AndersSjödahl, MikaelCasselgren, JohanMarklund, Pär

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