Change search
ReferencesLink to record
Permanent link

Direct link
Image Analysis in the Field of Oil Contamination Monitoring
Linköping University, Department of Electrical Engineering, Computer Vision.
2011 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Monitoring wear particles in lubricating oils allows specialists to evaluate thehealth and functionality of a mechanical system. The main analysis techniquesavailable today are manual particle analysis and automatic optical analysis. Man-ual particle analysis is effective and reliable since the analyst continuously seeswhat is being counted . The drawback is that the technique is quite time demand-ing and dependent of the skills of the analyst. Automatic optical particle countingconstitutes of a closed system not allowing for the objects counted to be observedin real-time. This has resulted in a number of sources of error for the instrument.In this thesis a new method for counting particles based on light microscopywith image analysis is proposed. It has proven to be a fast and effective methodthat eliminates the sources of error of the previously described methods. Thenew method correlates very well with manual analysis which is used as a refer-ence method throughout this study. Size estimation of particles and detectionof metallic particles has also shown to be possible with the current image analy-sis setup. With more advanced software and analysis instrumentation, the imageanalysis method could be further developed to a decision based machine allowingfor declarations about which wear mode is occurring in a mechanical system.

Place, publisher, year, edition, pages
2011. , 91 p.
Keyword [en]
contaminants in oil, counting particles, image analysis, oil condition monitoring, sizing particles, ISO4406, wear particles
National Category
Computer Vision and Robotics (Autonomous Systems)
URN: urn:nbn:se:liu:diva-68750ISRN: LITH-ISY-EX--11/4467--SEOAI: diva2:420518
Subject / course
Computer Vision Laboratory
2011-06-01, Algoritmen, Linköping University, Department of Electrical Engineering, Computer Vision Laboratory, SE-581 83 Linköping, Sweden, 08:15 (Swedish)
Available from: 2011-06-08 Created: 2011-06-01 Last updated: 2011-06-08Bibliographically approved

Open Access in DiVA

fulltext(6218 kB)874 downloads
File information
File name FULLTEXT01.pdfFile size 6218 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Ceco, Ema
By organisation
Computer Vision
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar
Total: 874 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 291 hits
ReferencesLink to record
Permanent link

Direct link