The main concern of this thesis was to investigate the running-in wear of automotive cam-follower systems used in the testing of lubricants and to develop wear particle analysis methods using image processing with particular reference to shape determination. Two kinds of cam-follower test rig were used to investigate the behaviour. The initial tests were carried out using a motored Peugeot TU3 cylinder head. The change in surface topography occurring through wear was examined as a basis for establishing an objective method of wear evaluation. The second series of tests was performed using a specially instrumented MIRA cam and tappet test machine. The effects of variations in the initial surface finish and hardness of the cams and followers were evaluated in which the effect of hardness difference between cam and follower and the implications of surface finish variation were highlighted. When compared with previous work, the measurement of the worn surface profiles of followers were similar to those predicted by a specific wear model for the situation where the cam was harder than the follower. Quantitative methods to analyse wear particle shape using image processing were developed. Appropriate image analysis hardware and associated computer software facilities were established to process data and provide quantitative information about particle size and shape, particularly edge detail. Wear particles taken from different sources were analysed. In the MIRA tests, when the cam was harder than the follower, particles generated under two body abrasion conditions exhibited a large aspect ratio and positive skewness, coupled to high kurtosis. This situation was contrasted by the smaller, rounder, rougher edged particles generated in the case where the cam was softer than the follower which exhibited a milder abrasive polishing type wear.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:639339 |
| Date | January 1991 |
| Creators | Wang, G-L. |
| Publisher | Swansea University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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