Principal component analysis of morphological descriptors for monitoring surface defects induced by thermal shock

2021 
Abstract Pattern recognition techniques are applied to various morphological descriptors to monitor the formation and propagation of surface defects of materials subjected to thermal shock. A low-cement high-alumina castable was synthesized, cured, sintered, and exposed to thermal stability testing using the water quench test. After a certain number of thermal shock cycles, photographs of the samples’ surfaces were taken and subjected to image analysis. The influence of the sintering temperature on the morphology of the detected defects was studied using principal component analysis (PCA) as a pattern recognition technique that is the most informative for extracting possible differences. The morphological descriptors of the defects correspond to the previous results regarding the influence of sintering temperature on the structure of a castable during thermal shocks.
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