A Python package for tribology research and education
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Updated
Nov 22, 2022 - Python
A Python package for tribology research and education
Long short-term memory based semi-supervised encoder-decoder for early prediction of failures in self-lubricating bearings
Work done by Liam Pond and Albert Kalayil on the oleic acid project in the Nanotribology Lab in 2024. Supervised by Drs. Philip Egberts, Vinay Saini, and Kasimuthumaniyan Subramanian.
Classification of progressive wear on a multi-directional pin-on-disc tribometer simulating conditions in human joints - UHMWPE against CoCrMo using Acoustic Emission and Machine Learning
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