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Influence Of Operational and Surface Conditions on the Tribological Performance of Self-Lubricating Polymer Composite Bearing Materials Used in Hydropower Applications
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0002-8533-897x
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0001-5080-0178
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0001-9110-2819
2019 (English)In: 74th STLE Annual Meeting and Exhibition: Program Guide and Schedule, Society of Tribologists and Lubrication Engineers (STLE) , 2019, p. 138-140Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

In hydropower applications, self-lubricating polymer composite bearings has proven to be a good and environmentally friendly replacement for the traditionally used grease lubricated bronze bearings. However, in recent years, end users have experienced several bearing failures due to more demanding operating conditions due to integration of fluctuating renewable energy sources, e.g. wind and solar power, into the electric power systems.

The aim of this work is to summarize and highlight important findings regarding the influence of various parameters on the tribological behaviour of these bearing materials using a linear reciprocating pin-on-disc configuration.

Results indicates that low sliding speed and high nominal pressure offer the best performance for these bearing materials, with a reduction in frictional loses with up to 45% and almost three times lower wear. Furthermore, friction and wear can be reduced even more by optimizing the surface topography and hardness of the shaft.

Place, publisher, year, edition, pages
Society of Tribologists and Lubrication Engineers (STLE) , 2019. p. 138-140
Keywords [en]
Sliding wear, Friction, Self-lubricating, Polymer composites
National Category
Other Mechanical Engineering
Research subject
Machine Elements
Identifiers
URN: urn:nbn:se:ltu:diva-74162OAI: oai:DiVA.org:ltu-74162DiVA, id: diva2:1320006
Conference
74th STLE Annual Meeting and Exhibition, Nashville, TN, USA, May 19-23, 2019
Available from: 2019-06-03 Created: 2019-06-03 Last updated: 2025-02-14Bibliographically approved

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Berglund, KimRodiouchkina, MariaLarsson, Roland

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