New surface characterization tools for alumina based refractory material exposed to cavitation - Image analysis and pattern recognition approach
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2018
Authors
Vuksanović, Marija M.Gajić-Kvaščev, Maja
Dojčinović, Marina
Volkov-Husović, Tatjana
Jančić-Heinemann, Radmila
Article (Published version)
,
© 2018 Elsevier Inc.
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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. © 2018 Elsevier Inc.
Keywords:
cavitation erosion / ceramic-matrix composite surface analysis / erosion testing / pattern recognitionSource:
Materials Characterization, 2018, 144, 113-119Funding / projects:
- 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)
- Predefined functional properties polymer composite materials processes and equipment development (RS-MESTD-Technological Development (TD or TR)-34011)
- 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; 1873-4189
WoS: 000447477300012
Scopus: 2-s2.0-85049600761
URI
https://linkinghub.elsevier.com/retrieve/pii/S1044580318313445https://vinar.vin.bg.ac.rs/handle/123456789/7771
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VinčaTY - JOUR AU - Vuksanović, Marija M. AU - Gajić-Kvaščev, Maja AU - Dojčinović, Marina AU - Volkov-Husović, Tatjana AU - Jančić-Heinemann, Radmila PY - 2018 UR - https://linkinghub.elsevier.com/retrieve/pii/S1044580318313445 UR - https://vinar.vin.bg.ac.rs/handle/123456789/7771 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. © 2018 Elsevier Inc. T2 - Materials Characterization T1 - New surface characterization tools for alumina based refractory material exposed to cavitation - Image analysis and pattern recognition approach VL - 144 SP - 113 EP - 119 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. © 2018 Elsevier Inc.", journal = "Materials Characterization", title = "New surface characterization tools for alumina based refractory material exposed to cavitation - Image analysis and pattern recognition approach", volume = "144", pages = "113-119", 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, 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 . .