Identification of Ancient Glass Components Based on Grey Correlation Analysis

Abstract

The article is based on mathematical modelling of the significant data of the two categorize glass specimen to examine the factors influencing the climate of the covering of the glass artefacts, to derive statistical patterns and correlations of the chemical composition content, on this basis, the subclasses are classified, and the accurate categorization manner applied to the analysis and discovery of glass composition is given. On the basis of data processing, the association between weathering of glass surface and glass kind, adornment and color is analyzed by using visual histogram. And it was found that the weathering of lead-barium glass was more serious than that of high-potassium glass, that B-grain decoration was easily weathered, and that black and light blue glass were the most severely weathered. The most significant effect on weathering is due to the content of silica in the lead-barium group, and the most significant effect on weathering is due to the content of sodium oxide in the high-potassium group. The correlations between the 14 chemical components in the two categories of high potassium glass and lead-barium glass were analysed by establishing a grey correlation analysis model, and the correlations between the different chemical components in the different categories were calculated and ranked. Similarly, the correlation between lead oxide and magnesium oxide was the highest in the high potassium group, while strontium oxide, tin oxide and sulphur dioxide were all less correlated, i.e. the correlation between this component and other chemical components was characterised by the ANOVA.