Wear of machine elements is the inevitable and anticipated consequence of surface contact between interacting machine parts such as shafts, bearings and gears, etc., which occurs even in properly lubricated systems. As component loading system investments and maintenance costs have risen, so the need for highly reliable and long-lasting systems has become very important. Wear particle morphology, allied to composition, can be used to monitor machine health conditions. Techniques used to determine morphological features of wear particles in indicating mode/mechanism of wear are mostly subjective ones. With the increasing "power" of computers and the use of image analysis, it is opportune to find some relationships between the quantitative morphological characteristics of wear particles found in circulating oil and the physical processes involved in generating them. The principal contribution arising from the results presented in this thesis is the underlying unique development of analysis methods, based on image processing and analysis, in conjunction with other physical means, to monitor the wear of rubbing contacts. Based on multi-variate statistical analysis, several different approaches were used to establish systematic wear particle identification processes. The combined use of shape factors, edge detail and size parameters was found to be superior to other previously proposed methods. This new approach was then used to differentiate wear particles quantitatively in terms of different wear situations, using an optical microscope-camera-image analysis system.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:638601 |
| Date | January 1995 |
| Creators | Raadnui, S. |
| Publisher | Swansea University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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