New surface characterization tools for alumina based refractory material exposed to cavitation - Image analysis and pattern recognition approach
Authorized Users Only
2018
Authors
Vuksanović, Marija M.Gajić-Kvaščev, Maja
Dojčinović, Marina
Volkov-Husović, Tatjana
Jančić-Heinemann, Radmila
Article (Published version)
Metadata
Show full item recordAbstract
The aim of this study was to examine the influence of cavitation erosion on the morphology of defects formed on the surfaces of alumina-based materials. The alumina-based samples were exposed to cavitation erosion for 42 min. The damages that occurred were monitored at predefined time intervals by measuring the mass loss and observing the sample surfaces. Digital images of surfaces were processed using an image analysis software package to define morphological characteristics of the damages occurred. The calculated morphological parameters were subjected to analysis by pattern recognition techniques to correlate the appearance of particular morphological characteristics with the behavior of the material during cavitation erosion. The newly established method in describing cavitation erosion which uses pattern recognition approach for treatments of morphological parameters calculated for damages by image analysis tools gave the results efficient for material characterization as the trad...itional one.
Keywords:
Cavitation erosion / Ceramic-matrix composite surface analysis / Erosion testing / Pattern recognitionSource:
Materials Characterization, 2018, 144, 113-119Publisher:
- Elsevier Science Inc, New York
Funding / projects:
- Predefined functional properties polymer composite materials processes and equipment development (RS-MESTD-Technological Development (TD or TR)-34011)
- Synthesis, processing and characterization of nanostructured materials for application in the field of energy, mechanical engineering, environmental protection and biomedicine (RS-MESTD-Integrated and Interdisciplinary Research (IIR or III)-45012)
- Research and verification of the multidisciplinary forensic methods in (RS-MESTD-Technological Development (TD or TR)-37021)
DOI: 10.1016/j.matchar.2018.07.003
ISSN: 1044-5803
WoS: 000447477300012
Scopus: 2-s2.0-85049600761
Institution/Community
Tehnološko-metalurški fakultetTY - JOUR AU - Vuksanović, Marija M. AU - Gajić-Kvaščev, Maja AU - Dojčinović, Marina AU - Volkov-Husović, Tatjana AU - Jančić-Heinemann, Radmila PY - 2018 UR - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/3927 AB - The aim of this study was to examine the influence of cavitation erosion on the morphology of defects formed on the surfaces of alumina-based materials. The alumina-based samples were exposed to cavitation erosion for 42 min. The damages that occurred were monitored at predefined time intervals by measuring the mass loss and observing the sample surfaces. Digital images of surfaces were processed using an image analysis software package to define morphological characteristics of the damages occurred. The calculated morphological parameters were subjected to analysis by pattern recognition techniques to correlate the appearance of particular morphological characteristics with the behavior of the material during cavitation erosion. The newly established method in describing cavitation erosion which uses pattern recognition approach for treatments of morphological parameters calculated for damages by image analysis tools gave the results efficient for material characterization as the traditional one. PB - Elsevier Science Inc, New York T2 - Materials Characterization T1 - New surface characterization tools for alumina based refractory material exposed to cavitation - Image analysis and pattern recognition approach EP - 119 SP - 113 VL - 144 DO - 10.1016/j.matchar.2018.07.003 ER -
@article{ author = "Vuksanović, Marija M. and Gajić-Kvaščev, Maja and Dojčinović, Marina and Volkov-Husović, Tatjana and Jančić-Heinemann, Radmila", year = "2018", abstract = "The aim of this study was to examine the influence of cavitation erosion on the morphology of defects formed on the surfaces of alumina-based materials. The alumina-based samples were exposed to cavitation erosion for 42 min. The damages that occurred were monitored at predefined time intervals by measuring the mass loss and observing the sample surfaces. Digital images of surfaces were processed using an image analysis software package to define morphological characteristics of the damages occurred. The calculated morphological parameters were subjected to analysis by pattern recognition techniques to correlate the appearance of particular morphological characteristics with the behavior of the material during cavitation erosion. The newly established method in describing cavitation erosion which uses pattern recognition approach for treatments of morphological parameters calculated for damages by image analysis tools gave the results efficient for material characterization as the traditional one.", publisher = "Elsevier Science Inc, New York", journal = "Materials Characterization", title = "New surface characterization tools for alumina based refractory material exposed to cavitation - Image analysis and pattern recognition approach", pages = "119-113", volume = "144", doi = "10.1016/j.matchar.2018.07.003" }
Vuksanović, M. M., Gajić-Kvaščev, M., Dojčinović, M., Volkov-Husović, T.,& Jančić-Heinemann, R.. (2018). New surface characterization tools for alumina based refractory material exposed to cavitation - Image analysis and pattern recognition approach. in Materials Characterization Elsevier Science Inc, New York., 144, 113-119. https://doi.org/10.1016/j.matchar.2018.07.003
Vuksanović MM, Gajić-Kvaščev M, Dojčinović M, Volkov-Husović T, Jančić-Heinemann R. New surface characterization tools for alumina based refractory material exposed to cavitation - Image analysis and pattern recognition approach. in Materials Characterization. 2018;144:113-119. doi:10.1016/j.matchar.2018.07.003 .
Vuksanović, Marija M., Gajić-Kvaščev, Maja, Dojčinović, Marina, Volkov-Husović, Tatjana, Jančić-Heinemann, Radmila, "New surface characterization tools for alumina based refractory material exposed to cavitation - Image analysis and pattern recognition approach" in Materials Characterization, 144 (2018):113-119, https://doi.org/10.1016/j.matchar.2018.07.003 . .